Scientific Method - Biology

Scientific Method - Biology

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1. Description of the Scientific Method

One of the goals of science is to come up with explanations about how the natural world (all the things we see or experience) functions. Although there are other systems for understanding and explaining the world around us (such as religion and traditional beliefs) science differs from these in that scientific explanations are based on laws of nature. Laws of nature are patterns in nature that are objective (do not depend on faith, authority, or opinion), are testable (can be demonstrated with experiments), and are consistent (the same conditions produce the same results).

The 4 Steps of the Scientific Method

To learn about the natural world, scientists use a four step procedure called the scientific method. The four steps of the scientific method are listed below. To help illustrate the scientific method, an example that an entomologist (a biologist who specializes in insects) might use is given in italics below each step.

Step 1: Observations & Questions

Observe something in the natural world and ask a question about how it works. The part of the natural world that is observed and investigated is usually the area that the scientist specializes in. An entomologist for example, would ask questions about how insects function.

“The life cycle of a fruit fly is about 30 days (at 29 degrees Celsius). How do changes in temperature affect the life cycle of a fruit fly?”

Step 2: Hypothesis

Make a hypothesis (an educated guess) which attempts to answer the question. A useful hypothesis is a testable statement.

“Decreasing the temperature of a fruit fly's environment will increase the time it takes the fruit fly to complete its life cycle.”

Step 3: Experiment

Design and carry out an experiment that is capable of testing the hypothesis. In other words, the experiment must be designed so that it will produce results that either clearly support or clearly falsify (disprove) the hypothesis. It helps to use “If-Then” predictions based on your hypothesis.

“Place 100 fruit flies at 18 degrees Celsius for one generation. Also place 100 fruit flies at 29 degrees Celsius for one generation. If the hypothesis is correct, then the fruit flies that develop at 18 degrees Celsius will complete their life cycle after those fruit flies that are placed at 29 degrees Celsius."

Step 4: Analyze Results and State Conclusions

Reject the hypothesis if the results are not consistent with the hypothesis or accept the hypothesis as possibly true if the results are consistent with the hypothesis. Notice that the hypothesis is not “proven to be true” even if the results do support it. This is because there may be explanations other than the hypothesis for the experimental result.

For example, if the fruit flies placed at 18 degrees Celsius do develop slower, it may be that their food is not as soft making it more difficult for the fruit flies to eat at the lower temperature, causing them to eat less food and thus grow slower.

If the experimental results do not support the hypothesis, the hypothesis may be modified and additional experiments may be done to test the new or revised hypothesis.

Figure (PageIndex{1}). (CC BY-NC-SA)

Designing a Good Experiment

The most challenging part of the scientific method is usually the third step, designing and carrying out an experiment to test the hypothesis. A well-designed experiment should include all of the following characteristics:

1. An independent variable. The independent variable is the part of the experiment that the scientist changes or manipulates to see what effect occurs.

“The temperature is the independent variable, since that is what the experiment changes to see its effect.”

2. A dependent variable. The dependent variable is the part of the experiment that changes because of the change in the independent variable. In other words, the dependent variable is the effect that occurs from changing the independent variable.

“The length of the fruit flies' life cycle is the dependent variable, since the time of development is expected to change because of the temperature.”

3. An experimental group. The experimental group is the group of subjects where the independent variable is set to an unusual or test level.

“The fruit flies placed at 18 degrees Celsius are the experimental group, since the effect of lower temperature on the life cycle of fruit flies is what is being tested.”

4. A control group. A control group is the group of subjects in the experiment that the experimental group is compared to. For the control group, the independent variable is set to a normal or usual level (which may be zero, if that is considered a normal level).

“The fruit flies kept at 29 degrees are the control group, since this is the optimal temperature for fruit fly development.”

Some experiments include things called positive controls and negative controls. These are slightly different than control groups. Positive and negative controls serve to show that the experiment is working correctly. A positive control is a part of the experiment that is deliberately designed to give a positive result. It shows that the experiment is capable of producing a positive result when it is supposed to. A negative control is a part of the experiment that is designed to give a negative result. It shows that the experiment is capable of producing a negative result when it is supposed to.

5. The experiment should contain repetition. This means that there should be more than one subject in the experimental group and the control group. Why? In general, the more repetition, the less likely that your results are due to random chance.

“The experimental group and the control group each contained 100 fruit flies.”

6. The experiment should be well defined. One aspect of “well defined” is that the procedure (the steps) must be written down and clearly described. The true test of a well written experimental procedure is that another scientist could duplicate it exactly using just the written directions. Another aspect of “well defined” is that everything in the experiment, such as the materials, chemicals, equipment, environmental conditions, and the subjects (the organisms involved in the experiment), should be described as exactly as possible. All of the factors that are kept equal in the experiment and control groups are called standardized variables. Another aspect of “well defined” is that all parts of the experiment should be quantified. This means they should be measured by numbers.

a) All fruit flies in this experiment are the same species (Drosophila melanogaster). All fruit flies were placed in plastic vials with standard cornmeal media and a cotton stopper. All fruit flies received artificial sunlight for 16 hours per day.

b) One group of 100 fruit flies (the experimental group) were placed in an incubator set to 18 degrees Celsius.

c) One group of 100 fruit flies (the control group) were placed in an incubator set to 29 degrees Celsius.

d) In order to accurately determine the length of the life cycle of the fruit flies, 100 adult flies were allowed to lay eggs for 2 days and then removed from vials. Vials were monitored daily to determine the stage of the life cycle of the offspring of the original adult fruit flies. The end of the life cycle was recorded as the time when half of the fruit flies had undergone eclosion (adults emerge from the pupa case).

What is a Scientific Theory?

"It's just a theory." Our everyday use of the term theory often implies a mere guess or something that is unproven. However, a scientific theory implies that something has been proven and is generally accepted as being true. A scientific theory is an explanation for natural events that is based on a large number of observations and has been verified multiple times. Theories help scientists to explain large amounts of data.

A theory differs from a hypothesis in that it is much broader in scope and supported by a much greater body of evidence. Remember, a hypothesis is an educated guess that is based upon observation, but has not yet been proven.

While theories are not easily discarded, as they are based on a large body evidence, sometimes scientists must modify or even reject scientific theories when new research methods produce results that do not fit with the current theory.

Scientific Method Tutorial by Dr. Katherine Harris is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.

This tutorial was funded by the Title V-STEM Grant #P031S090007.


Important debates in the history of science concern rationalism, especially as advocated by René Descartes inductivism and/or empiricism, as argued for by Francis Bacon, and rising to particular prominence with Isaac Newton and his followers and hypothetico-deductivism, which came to the fore in the early 19th century.

The term "scientific method" emerged in the 19th century, when a significant institutional development of science was taking place and terminologies establishing clear boundaries between science and non-science, such as "scientist" and "pseudoscience", appeared. [16] Throughout the 1830s and 1850s, by which time Baconianism was popular, naturalists like William Whewell, John Herschel, John Stuart Mill engaged in debates over "induction" and "facts" and were focused on how to generate knowledge. [16] In the late 19th and early 20th centuries, a debate over realism vs. antirealism was conducted as powerful scientific theories extended beyond the realm of the observable. [17]

The term "scientific method" came into popular use in the twentieth century, popping up in dictionaries and science textbooks, although there was little scientific consensus over its meaning. [16] Although there was growth through the middle of the twentieth century, by the 1960s and 1970s numerous influential philosophers of science such as Thomas Kuhn and Paul Feyerabend had questioned the universality of the "scientific method" and in doing so largely replaced the notion of science as a homogeneous and universal method with that of it being a heterogeneous and local practice. [16] In particular, Paul Feyerabend, in the 1975 first edition of his book Against Method, argued against there being any universal rules of science. [17] Later examples include physicist Lee Smolin's 2013 essay "There Is No Scientific Method" [18] and historian of science Daniel Thurs's chapter in the 2015 book Newton's Apple and Other Myths about Science, which concluded that the scientific method is a myth or, at best, an idealization. [19] Philosophers Robert Nola and Howard Sankey, in their 2007 book Theories of Scientific Method, said that debates over scientific method continue, and argued that Feyerabend, despite the title of Against Method, accepted certain rules of method and attempted to justify those rules with a meta methodology. [20]

The scientific method is the process by which science is carried out. [21] As in other areas of inquiry, science (through the scientific method) can build on previous knowledge and develop a more sophisticated understanding of its topics of study over time. [22] [23] [24] [25] [26] [27] This model can be seen to underlie the scientific revolution. [28]

The ubiquitous element in the scientific method is empiricism. This is in opposition to stringent forms of rationalism: the scientific method embodies that reason alone cannot solve a particular scientific problem. A strong formulation of the scientific method is not always aligned with a form of empiricism in which the empirical data is put forward in the form of experience or other abstracted forms of knowledge in current scientific practice, however, the use of scientific modelling and reliance on abstract typologies and theories is normally accepted. The scientific method is of necessity also an expression of an opposition to claims that e.g. revelation, political or religious dogma, appeals to tradition, commonly held beliefs, common sense, or, importantly, currently held theories, are the only possible means of demonstrating truth.

Different early expressions of empiricism and the scientific method can be found throughout history, for instance with the ancient Stoics, Epicurus, [29] Alhazen, [30] Roger Bacon, and William of Ockham. From the 16th century onwards, experiments were advocated by Francis Bacon, and performed by Giambattista della Porta, [31] Johannes Kepler, [32] and Galileo Galilei. [33] There was particular development aided by theoretical works by Francisco Sanches, [34] John Locke, George Berkeley, and David Hume.

The hypothetico-deductive model [35] formulated in the 20th century, is the ideal although it has undergone significant revision since first proposed (for a more formal discussion, see § Elements of the scientific method). Staddon (2017) argues it is a mistake to try following rules [36] which are best learned through careful study of examples of scientific investigation.


The overall process involves making conjectures (hypotheses), deriving predictions from them as logical consequences, and then carrying out experiments based on those predictions to determine whether the original conjecture was correct. [4] There are difficulties in a formulaic statement of method, however. Though the scientific method is often presented as a fixed sequence of steps, these actions are better considered as general principles. [9] Not all steps take place in every scientific inquiry (nor to the same degree), and they are not always done in the same order. As noted by scientist and philosopher William Whewell (1794–1866), "invention, sagacity, [and] genius" [10] are required at every step.

Formulation of a question

The question can refer to the explanation of a specific observation, as in "Why is the sky blue?" but can also be open-ended, as in "How can I design a drug to cure this particular disease?" This stage frequently involves finding and evaluating evidence from previous experiments, personal scientific observations or assertions, as well as the work of other scientists. If the answer is already known, a different question that builds on the evidence can be posed. When applying the scientific method to research, determining a good question can be very difficult and it will affect the outcome of the investigation. [37]


A hypothesis is a conjecture, based on knowledge obtained while formulating the question, that may explain any given behavior. The hypothesis might be very specific for example, Einstein's equivalence principle or Francis Crick's "DNA makes RNA makes protein", [38] or it might be broad for example, unknown species of life dwell in the unexplored depths of the oceans. A statistical hypothesis is a conjecture about a given statistical population. For example, the population might be people with a particular disease. The conjecture might be that a new drug will cure the disease in some of those people. Terms commonly associated with statistical hypotheses are null hypothesis and alternative hypothesis. A null hypothesis is the conjecture that the statistical hypothesis is false for example, that the new drug does nothing and that any cure is caused by chance. Researchers normally want to show that the null hypothesis is false. The alternative hypothesis is the desired outcome, that the drug does better than chance. A final point: a scientific hypothesis must be falsifiable, meaning that one can identify a possible outcome of an experiment that conflicts with predictions deduced from the hypothesis otherwise, it cannot be meaningfully tested.


This step involves determining the logical consequences of the hypothesis. One or more predictions are then selected for further testing. The more unlikely that a prediction would be correct simply by coincidence, then the more convincing it would be if the prediction were fulfilled the evidence is also stronger if the answer to the prediction is not already known, due to the effects of hindsight bias (see also postdiction). Ideally, the prediction must also distinguish the hypothesis from likely alternatives if two hypotheses make the same prediction, observing the prediction to be correct is not evidence for either one over the other. (These statements about the relative strength of evidence can be mathematically derived using Bayes' Theorem). [39]


This is an investigation of whether the real world behaves as predicted by the hypothesis. Scientists (and other people) test hypotheses by conducting experiments. The purpose of an experiment is to determine whether observations of the real world agree with or conflict with the predictions derived from a hypothesis. If they agree, confidence in the hypothesis increases otherwise, it decreases. The agreement does not assure that the hypothesis is true future experiments may reveal problems. Karl Popper advised scientists to try to falsify hypotheses, i.e., to search for and test those experiments that seem most doubtful. Large numbers of successful confirmations are not convincing if they arise from experiments that avoid risk. [7] Experiments should be designed to minimize possible errors, especially through the use of appropriate scientific controls. For example, tests of medical treatments are commonly run as double-blind tests. Test personnel, who might unwittingly reveal to test subjects which samples are the desired test drugs and which are placebos, are kept ignorant of which are which. Such hints can bias the responses of the test subjects. Furthermore, failure of an experiment does not necessarily mean the hypothesis is false. Experiments always depend on several hypotheses, e.g., that the test equipment is working properly, and a failure may be a failure of one of the auxiliary hypotheses. (See the Duhem–Quine thesis.) Experiments can be conducted in a college lab, on a kitchen table, at CERN's Large Hadron Collider, at the bottom of an ocean, on Mars (using one of the working rovers), and so on. Astronomers do experiments, searching for planets around distant stars. Finally, most individual experiments address highly specific topics for reasons of practicality. As a result, evidence about broader topics is usually accumulated gradually.


This involves determining what the results of the experiment show and deciding on the next actions to take. The predictions of the hypothesis are compared to those of the null hypothesis, to determine which is better able to explain the data. In cases where an experiment is repeated many times, a statistical analysis such as a chi-squared test may be required. If the evidence has falsified the hypothesis, a new hypothesis is required if the experiment supports the hypothesis but the evidence is not strong enough for high confidence, other predictions from the hypothesis must be tested. Once a hypothesis is strongly supported by evidence, a new question can be asked to provide further insight on the same topic. Evidence from other scientists and experience are frequently incorporated at any stage in the process. Depending on the complexity of the experiment, many iterations may be required to gather sufficient evidence to answer a question with confidence or to build up many answers to highly specific questions to answer a single broader question.

DNA example

The basic elements of the scientific method are illustrated by the following example from the discovery of the structure of DNA:

  • Question: Previous investigation of DNA had determined its chemical composition (the four nucleotides), the structure of each individual nucleotide, and other properties. X-ray diffraction patterns of DNA by Florence Bell in her Ph.D. thesis (1939) were similar to (although not as good as) "photo 51", but this research was interrupted by the events of World War II. DNA had been identified as the carrier of genetic information by the Avery–MacLeod–McCarty experiment in 1944, [40] but the mechanism of how genetic information was stored in DNA was unclear.
  • Hypothesis: Linus Pauling, Francis Crick and James D. Watson hypothesized that DNA had a helical structure. [41]
  • Prediction: If DNA had a helical structure, its X-ray diffraction pattern would be X-shaped. [42][43] This prediction was determined using the mathematics of the helix transform, which had been derived by Cochran, Crick, and Vand [44] (and independently by Stokes). This prediction was a mathematical construct, completely independent from the biological problem at hand.
  • Experiment: Rosalind Franklin used pure DNA to perform X-ray diffraction to produce photo 51. The results showed an X-shape.
  • Analysis: When Watson saw the detailed diffraction pattern, he immediately recognized it as a helix. [45][46] He and Crick then produced their model, using this information along with the previously known information about DNA's composition, especially Chargaff's rules of base pairing. [47]

The discovery became the starting point for many further studies involving the genetic material, such as the field of molecular genetics, and it was awarded the Nobel Prize in 1962. Each step of the example is examined in more detail later in the article.

Other components

The scientific method also includes other components required even when all the iterations of the steps above have been completed: [48]


If an experiment cannot be repeated to produce the same results, this implies that the original results might have been in error. As a result, it is common for a single experiment to be performed multiple times, especially when there are uncontrolled variables or other indications of experimental error. For significant or surprising results, other scientists may also attempt to replicate the results for themselves, especially if those results would be important to their own work. [49] Replication has become a contentious issue in social and biomedical science where treatments are administered to groups of individuals. Typically an experimental group gets the treatment, such as a drug, and the control group gets a placebo. John Ioannidis in 2005 pointed out that the method being used has led to many findings that cannot be replicated. [50]

External review

The process of peer review involves evaluation of the experiment by experts, who typically give their opinions anonymously. Some journals request that the experimenter provide lists of possible peer reviewers, especially if the field is highly specialized. Peer review does not certify the correctness of the results, only that, in the opinion of the reviewer, the experiments themselves were sound (based on the description supplied by the experimenter). If the work passes peer review, which occasionally may require new experiments requested by the reviewers, it will be published in a peer-reviewed scientific journal. The specific journal that publishes the results indicates the perceived quality of the work. [51]

Data recording and sharing

Scientists typically are careful in recording their data, a requirement promoted by Ludwik Fleck (1896–1961) and others. [52] Though not typically required, they might be requested to supply this data to other scientists who wish to replicate their original results (or parts of their original results), extending to the sharing of any experimental samples that may be difficult to obtain. [53]

Scientific inquiry generally aims to obtain knowledge in the form of testable explanations that scientists can use to predict the results of future experiments. This allows scientists to gain a better understanding of the topic under study, and later to use that understanding to intervene in its causal mechanisms (such as to cure disease). The better an explanation is at making predictions, the more useful it frequently can be, and the more likely it will continue to explain a body of evidence better than its alternatives. The most successful explanations – those which explain and make accurate predictions in a wide range of circumstances – are often called scientific theories.

Most experimental results do not produce large changes in human understanding improvements in theoretical scientific understanding typically result from a gradual process of development over time, sometimes across different domains of science. [54] Scientific models vary in the extent to which they have been experimentally tested and for how long, and in their acceptance in the scientific community. In general, explanations become accepted over time as evidence accumulates on a given topic, and the explanation in question proves more powerful than its alternatives at explaining the evidence. Often subsequent researchers re-formulate the explanations over time, or combined explanations to produce new explanations.

Tow sees the scientific method in terms of an evolutionary algorithm applied to science and technology. [55]

Properties of scientific inquiry

Scientific knowledge is closely tied to empirical findings and can remain subject to falsification if new experimental observations are incompatible with what is found. That is, no theory can ever be considered final since new problematic evidence might be discovered. If such evidence is found, a new theory may be proposed, or (more commonly) it is found that modifications to the previous theory are sufficient to explain the new evidence. The strength of a theory can be argued [ by whom? ] to relate to how long it has persisted without major alteration to its core principles.

Theories can also become subsumed by other theories. For example, Newton's laws explained thousands of years of scientific observations of the planets almost perfectly. However, these laws were then determined to be special cases of a more general theory (relativity), which explained both the (previously unexplained) exceptions to Newton's laws and predicted and explained other observations such as the deflection of light by gravity. Thus, in certain cases independent, unconnected, scientific observations can be connected, unified by principles of increasing explanatory power. [56] [57]

Since new theories might be more comprehensive than what preceded them, and thus be able to explain more than previous ones, successor theories might be able to meet a higher standard by explaining a larger body of observations than their predecessors. [56] For example, the theory of evolution explains the diversity of life on Earth, how species adapt to their environments, and many other patterns observed in the natural world [58] [59] its most recent major modification was unification with genetics to form the modern evolutionary synthesis. In subsequent modifications, it has also subsumed aspects of many other fields such as biochemistry and molecular biology.

Beliefs and biases

Scientific methodology often directs that hypotheses be tested in controlled conditions wherever possible. This is frequently possible in certain areas, such as in the biological sciences, and more difficult in other areas, such as in astronomy.

The practice of experimental control and reproducibility can have the effect of diminishing the potentially harmful effects of circumstance, and to a degree, personal bias. For example, pre-existing beliefs can alter the interpretation of results, as in confirmation bias this is a heuristic that leads a person with a particular belief to see things as reinforcing their belief, even if another observer might disagree (in other words, people tend to observe what they expect to observe).

A historical example is the belief that the legs of a galloping horse are splayed at the point when none of the horse's legs touch the ground, to the point of this image being included in paintings by its supporters. However, the first stop-action pictures of a horse's gallop by Eadweard Muybridge showed this to be false, and that the legs are instead gathered together. [60]

Another important human bias that plays a role is a preference for new, surprising statements (see appeal to novelty), which can result in a search for evidence that the new is true. [61] Poorly attested beliefs can be believed and acted upon via a less rigorous heuristic. [62]

Goldhaber and Nieto published in 2010 the observation that if theoretical structures with "many closely neighboring subjects are described by connecting theoretical concepts, then the theoretical structure acquires a robustness which makes it increasingly hard – though certainly never impossible – to overturn". [57] When a narrative is constructed its elements become easier to believe. [63] For more on the narrative fallacy, see also Fleck 1979, p. 27: "Words and ideas are originally phonetic and mental equivalences of the experiences coinciding with them. . Such proto-ideas are at first always too broad and insufficiently specialized. . Once a structurally complete and closed system of opinions consisting of many details and relations has been formed, it offers enduring resistance to anything that contradicts it." Sometimes, these have their elements assumed a priori, or contain some other logical or methodological flaw in the process that ultimately produced them. Donald M. MacKay has analyzed these elements in terms of limits to the accuracy of measurement and has related them to instrumental elements in a category of measurement. [64]

There are different ways of outlining the basic method used for scientific inquiry. The scientific community and philosophers of science generally agree on the following classification of method components. These methodological elements and organization of procedures tend to be more characteristic of natural sciences than social sciences. Nonetheless, the cycle of formulating hypotheses, testing and analyzing the results, and formulating new hypotheses, will resemble the cycle described below.

The scientific method is an iterative, cyclical process through which information is continually revised. [65] [66] It is generally recognized to develop advances in knowledge through the following elements, in varying combinations or contributions: [67] [68]

  • Characterizations (observations, definitions, and measurements of the subject of inquiry)
  • Hypotheses (theoretical, hypothetical explanations of observations and measurements of the subject)
  • Predictions (inductive and deductive reasoning from the hypothesis or theory)
  • Experiments (tests of all of the above)

Each element of the scientific method is subject to peer review for possible mistakes. These activities do not describe all that scientists do but apply mostly to experimental sciences (e.g., physics, chemistry, and biology). The elements above are often taught in the educational system as "the scientific method". [69]

The scientific method is not a single recipe: it requires intelligence, imagination, and creativity. [70] In this sense, it is not a mindless set of standards and procedures to follow, but is rather an ongoing cycle, constantly developing more useful, accurate, and comprehensive models and methods. For example, when Einstein developed the Special and General Theories of Relativity, he did not in any way refute or discount Newton's Principia. On the contrary, if the astronomically massive, the feather-light, and the extremely fast are removed from Einstein's theories – all phenomena Newton could not have observed – Newton's equations are what remain. Einstein's theories are expansions and refinements of Newton's theories and, thus, increase confidence in Newton's work.

A linearized, pragmatic scheme of the four points above is sometimes offered as a guideline for proceeding: [71]

  1. Define a question
  2. Gather information and resources (observe)
  3. Form an explanatory hypothesis
  4. Test the hypothesis by performing an experiment and collecting data in a reproducible manner
  5. Analyze the data
  6. Interpret the data and draw conclusions that serve as a starting point for a new hypothesis
  7. Publish results
  8. Retest (frequently done by other scientists)

The iterative cycle inherent in this step-by-step method goes from point 3 to 6 back to 3 again.

While this schema outlines a typical hypothesis/testing method, [72] many philosophers, historians, and sociologists of science, including Paul Feyerabend, claim that such descriptions of scientific method have little relation to the ways that science is actually practiced.


The scientific method depends upon increasingly sophisticated characterizations of the subjects of investigation. (The subjects can also be called unsolved problems or the unknowns.) For example, Benjamin Franklin conjectured, correctly, that St. Elmo's fire was electrical in nature, but it has taken a long series of experiments and theoretical changes to establish this. While seeking the pertinent properties of the subjects, careful thought may also entail some definitions and observations the observations often demand careful measurements and/or counting.

The systematic, careful collection of measurements or counts of relevant quantities is often the critical difference between pseudo-sciences, such as alchemy, and science, such as chemistry or biology. Scientific measurements are usually tabulated, graphed, or mapped, and statistical manipulations, such as correlation and regression, performed on them. The measurements might be made in a controlled setting, such as a laboratory, or made on more or less inaccessible or unmanipulatable objects such as stars or human populations. The measurements often require specialized scientific instruments such as thermometers, spectroscopes, particle accelerators, or voltmeters, and the progress of a scientific field is usually intimately tied to their invention and improvement.

I am not accustomed to saying anything with certainty after only one or two observations.


Measurements in scientific work are also usually accompanied by estimates of their uncertainty. The uncertainty is often estimated by making repeated measurements of the desired quantity. Uncertainties may also be calculated by consideration of the uncertainties of the individual underlying quantities used. Counts of things, such as the number of people in a nation at a particular time, may also have an uncertainty due to data collection limitations. Or counts may represent a sample of desired quantities, with an uncertainty that depends upon the sampling method used and the number of samples taken.


Measurements demand the use of operational definitions of relevant quantities. That is, a scientific quantity is described or defined by how it is measured, as opposed to some more vague, inexact, or "idealized" definition. For example, electric current, measured in amperes, may be operationally defined in terms of the mass of silver deposited in a certain time on an electrode in an electrochemical device that is described in some detail. The operational definition of a thing often relies on comparisons with standards: the operational definition of "mass" ultimately relies on the use of an artifact, such as a particular kilogram of platinum-iridium kept in a laboratory in France.

The scientific definition of a term sometimes differs substantially from its natural language usage. For example, mass and weight overlap in meaning in common discourse, but have distinct meanings in mechanics. Scientific quantities are often characterized by their units of measure which can later be described in terms of conventional physical units when communicating the work.

New theories are sometimes developed after realizing certain terms have not previously been sufficiently clearly defined. For example, Albert Einstein's first paper on relativity begins by defining simultaneity and the means for determining length. These ideas were skipped over by Isaac Newton with, "I do not define time, space, place and motion, as being well known to all." Einstein's paper then demonstrates that they (viz., absolute time and length independent of motion) were approximations. Francis Crick cautions us that when characterizing a subject, however, it can be premature to define something when it remains ill-understood. [74] In Crick's study of consciousness, he actually found it easier to study awareness in the visual system, rather than to study free will, for example. His cautionary example was the gene the gene was much more poorly understood before Watson and Crick's pioneering discovery of the structure of DNA it would have been counterproductive to spend much time on the definition of the gene, before them.


The history of the discovery of the structure of DNA is a classic example of the elements of the scientific method: in 1950 it was known that genetic inheritance had a mathematical description, starting with the studies of Gregor Mendel, and that DNA contained genetic information (Oswald Avery's transforming principle). [40] But the mechanism of storing genetic information (i.e., genes) in DNA was unclear. Researchers in Bragg's laboratory at Cambridge University made X-ray diffraction pictures of various molecules, starting with crystals of salt, and proceeding to more complicated substances. Using clues painstakingly assembled over decades, beginning with its chemical composition, it was determined that it should be possible to characterize the physical structure of DNA, and the X-ray images would be the vehicle. [75] ..2. DNA-hypotheses

Another example: precession of Mercury

The characterization element can require extended and extensive study, even centuries. It took thousands of years of measurements, from the Chaldean, Indian, Persian, Greek, Arabic, and European astronomers, to fully record the motion of planet Earth. Newton was able to include those measurements into the consequences of his laws of motion. But the perihelion of the planet Mercury's orbit exhibits a precession that cannot be fully explained by Newton's laws of motion (see diagram to the right), as Leverrier pointed out in 1859. The observed difference for Mercury's precession between Newtonian theory and observation was one of the things that occurred to Albert Einstein as a possible early test of his theory of General relativity. His relativistic calculations matched observation much more closely than did Newtonian theory. The difference is approximately 43 arc-seconds per century.

Hypothesis development

A hypothesis is a suggested explanation of a phenomenon, or alternately a reasoned proposal suggesting a possible correlation between or among a set of phenomena.

Normally hypotheses have the form of a mathematical model. Sometimes, but not always, they can also be formulated as existential statements, stating that some particular instance of the phenomenon being studied has some characteristic and causal explanations, which have the general form of universal statements, stating that every instance of the phenomenon has a particular characteristic.

Scientists are free to use whatever resources they have – their own creativity, ideas from other fields, inductive reasoning, Bayesian inference, and so on – to imagine possible explanations for a phenomenon under study. Albert Einstein once observed that "there is no logical bridge between phenomena and their theoretical principles." [77] Charles Sanders Peirce, borrowing a page from Aristotle (Prior Analytics, 2.25) described the incipient stages of inquiry, instigated by the "irritation of doubt" to venture a plausible guess, as abductive reasoning. The history of science is filled with stories of scientists claiming a "flash of inspiration", or a hunch, which then motivated them to look for evidence to support or refute their idea. Michael Polanyi made such creativity the centerpiece of his discussion of methodology.

the success of a hypothesis, or its service to science, lies not simply in its perceived "truth", or power to displace, subsume or reduce a predecessor idea, but perhaps more in its ability to stimulate the research that will illuminate . bald suppositions and areas of vagueness.

In general scientists tend to look for theories that are "elegant" or "beautiful". Scientists often use these terms to refer to a theory that is following the known facts but is nevertheless relatively simple and easy to handle. Occam's Razor serves as a rule of thumb for choosing the most desirable amongst a group of equally explanatory hypotheses.

To minimize the confirmation bias which results from entertaining a single hypothesis, strong inference emphasizes the need for entertaining multiple alternative hypotheses. [79]


Linus Pauling proposed that DNA might be a triple helix. [80] This hypothesis was also considered by Francis Crick and James D. Watson but discarded. When Watson and Crick learned of Pauling's hypothesis, they understood from existing data that Pauling was wrong [81] and that Pauling would soon admit his difficulties with that structure. So, the race was on to figure out the correct structure (except that Pauling did not realize at the time that he was in a race) ..3. DNA-predictions

Predictions from the hypothesis

Any useful hypothesis will enable predictions, by reasoning including deductive reasoning. It might predict the outcome of an experiment in a laboratory setting or the observation of a phenomenon in nature. The prediction can also be statistical and deal only with probabilities.

It is essential that the outcome of testing such a prediction be currently unknown. Only in this case does a successful outcome increase the probability that the hypothesis is true. If the outcome is already known, it is called a consequence and should have already been considered while formulating the hypothesis.

If the predictions are not accessible by observation or experience, the hypothesis is not yet testable and so will remain to that extent unscientific in a strict sense. A new technology or theory might make the necessary experiments feasible. For example, while a hypothesis on the existence of other intelligent species may be convincing with scientifically based speculation, no known experiment can test this hypothesis. Therefore, science itself can have little to say about the possibility. In the future, a new technique may allow for an experimental test and the speculation would then become part of accepted science.


James D. Watson, Francis Crick, and others hypothesized that DNA had a helical structure. This implied that DNA's X-ray diffraction pattern would be 'x shaped'. [43] [82] This prediction followed from the work of Cochran, Crick and Vand [44] (and independently by Stokes). The Cochran-Crick-Vand-Stokes theorem provided a mathematical explanation for the empirical observation that diffraction from helical structures produces x shaped patterns.

In their first paper, Watson and Crick also noted that the double helix structure they proposed provided a simple mechanism for DNA replication, writing, "It has not escaped our notice that the specific pairing we have postulated immediately suggests a possible copying mechanism for the genetic material". [83] ..4. DNA-experiments

Another example: general relativity

Einstein's theory of general relativity makes several specific predictions about the observable structure of spacetime, such as that light bends in a gravitational field, and that the amount of bending depends in a precise way on the strength of that gravitational field. Arthur Eddington's observations made during a 1919 solar eclipse supported General Relativity rather than Newtonian gravitation. [84]


Once predictions are made, they can be sought by experiments. If the test results contradict the predictions, the hypotheses which entailed them are called into question and become less tenable. Sometimes the experiments are conducted incorrectly or are not very well designed when compared to a crucial experiment. If the experimental results confirm the predictions, then the hypotheses are considered more likely to be correct, but might still be wrong and continue to be subject to further testing. The experimental control is a technique for dealing with observational error. This technique uses the contrast between multiple samples (or observations) under differing conditions to see what varies or what remains the same. We vary the conditions for each measurement, to help isolate what has changed. Mill's canons can then help us figure out what the important factor is. [85] Factor analysis is one technique for discovering the important factor in an effect.

Depending on the predictions, the experiments can have different shapes. It could be a classical experiment in a laboratory setting, a double-blind study or an archaeological excavation. Even taking a plane from New York to Paris is an experiment that tests the aerodynamical hypotheses used for constructing the plane.

Scientists assume an attitude of openness and accountability on the part of those experimenting. Detailed record-keeping is essential, to aid in recording and reporting on the experimental results, and supports the effectiveness and integrity of the procedure. They will also assist in reproducing the experimental results, likely by others. Traces of this approach can be seen in the work of Hipparchus (190–120 BCE), when determining a value for the precession of the Earth, while controlled experiments can be seen in the works of al-Battani [86] [ better source needed ] (853–929) and Alhazen (965–1039). [87] : p.444 for his experiments on color


Watson and Crick showed an initial (and incorrect) proposal for the structure of DNA to a team from Kings College – Rosalind Franklin, Maurice Wilkins, and Raymond Gosling. Franklin immediately spotted the flaws which concerned the water content. Later Watson saw Franklin's detailed X-ray diffraction images which showed an X-shape [88] and was able to confirm the structure was helical. [45] [46] This rekindled Watson and Crick's model building and led to the correct structure. ..1. DNA-characterizations

Evaluation and improvement

The scientific method is iterative. At any stage, it is possible to refine its accuracy and precision, so that some consideration will lead the scientist to repeat an earlier part of the process. Failure to develop an interesting hypothesis may lead a scientist to re-define the subject under consideration. Failure of a hypothesis to produce interesting and testable predictions may lead to reconsideration of the hypothesis or of the definition of the subject. Failure of an experiment to produce interesting results may lead a scientist to reconsider the experimental method, the hypothesis, or the definition of the subject.

Other scientists may start their own research and enter the process at any stage. They might adopt the characterization and formulate their own hypothesis, or they might adopt the hypothesis and deduce their own predictions. Often the experiment is not done by the person who made the prediction, and the characterization is based on experiments done by someone else. Published results of experiments can also serve as a hypothesis predicting their own reproducibility.


After considerable fruitless experimentation, being discouraged by their superior from continuing, and numerous false starts, [89] [90] [91] Watson and Crick were able to infer the essential structure of DNA by concrete modeling of the physical shapes of the nucleotides which comprise it. [47] [92] They were guided by the bond lengths which had been deduced by Linus Pauling and by Rosalind Franklin's X-ray diffraction images. ..DNA Example


Science is a social enterprise, and scientific work tends to be accepted by the scientific community when it has been confirmed. Crucially, experimental and theoretical results must be reproduced by others within the scientific community. Researchers have given their lives for this vision Georg Wilhelm Richmann was killed by ball lightning (1753) when attempting to replicate the 1752 kite-flying experiment of Benjamin Franklin. [93]

To protect against bad science and fraudulent data, government research-granting agencies such as the National Science Foundation, and science journals, including Nature and Science, have a policy that researchers must archive their data and methods so that other researchers can test the data and methods and build on the research that has gone before. Scientific data archiving can be done at several national archives in the U.S. or the World Data Center.

Classical model

The classical model of scientific inquiry derives from Aristotle, [94] who distinguished the forms of approximate and exact reasoning, set out the threefold scheme of abductive, deductive, and inductive inference, and also treated the compound forms such as reasoning by analogy.

Hypothetico-deductive model

The hypothetico-deductive model or method is a proposed description of the scientific method. Here, predictions from the hypothesis are central: if you assume the hypothesis to be true, what consequences follow?

If a subsequent empirical investigation does not demonstrate that these consequences or predictions correspond to the observable world, the hypothesis can be concluded to be false.

Pragmatic model

In 1877, [22] Charles Sanders Peirce (1839–1914) characterized inquiry in general not as the pursuit of truth per se but as the struggle to move from irritating, inhibitory doubts born of surprises, disagreements, and the like, and to reach a secure belief, the belief being that on which one is prepared to act. He framed scientific inquiry as part of a broader spectrum and as spurred, like inquiry generally, by actual doubt, not mere verbal or hyperbolic doubt, which he held to be fruitless. [95] He outlined four methods of settling opinion, ordered from least to most successful:

  1. The method of tenacity (policy of sticking to initial belief) – which brings comforts and decisiveness but leads to trying to ignore contrary information and others' views as if truth were intrinsically private, not public. It goes against the social impulse and easily falters since one may well notice when another's opinion is as good as one's own initial opinion. Its successes can shine but tend to be transitory. [96]
  2. The method of authority – which overcomes disagreements but sometimes brutally. Its successes can be majestic and long-lived, but it cannot operate thoroughly enough to suppress doubts indefinitely, especially when people learn of other societies' present and past.
  3. The method of the a priori – which promotes conformity less brutally but fosters opinions as something like tastes, arising in conversation and comparisons of perspectives in terms of "what is agreeable to reason." Thereby it depends on fashion in paradigms and goes in circles over time. It is more intellectual and respectable but, like the first two methods, sustains accidental and capricious beliefs, destining some minds to doubt it.
  4. The scientific method – the method wherein inquiry regards itself as fallible and purposely tests itself and criticizes, corrects, and improves itself.

Peirce held that slow, stumbling ratiocination can be dangerously inferior to instinct and traditional sentiment in practical matters, and that the scientific method is best suited to theoretical research, [97] which in turn should not be trammeled by the other methods and practical ends reason's "first rule" is that, in order to learn, one must desire to learn and, as a corollary, must not block the way of inquiry. [98] The scientific method excels the others by being deliberately designed to arrive – eventually – at the most secure beliefs, upon which the most successful practices can be based. Starting from the idea that people seek not truth per se but instead to subdue irritating, inhibitory doubt, Peirce showed how, through the struggle, some can come to submit to the truth for the sake of belief's integrity, seek as truth the guidance of potential practice correctly to its given goal, and wed themselves to the scientific method. [22] [25]

For Peirce, rational inquiry implies presuppositions about truth and the real to reason is to presuppose (and at least to hope), as a principle of the reasoner's self-regulation, that the real is discoverable and independent of our vagaries of opinion. In that vein, he defined truth as the correspondence of a sign (in particular, a proposition) to its object and, pragmatically, not as the actual consensus of some definite, finite community (such that to inquire would be to poll the experts), but instead as that final opinion which all investigators would reach sooner or later but still inevitably, if they were to push investigation far enough, even when they start from different points. [99] In tandem he defined the real as a true sign's object (be that object a possibility or quality, or an actuality or brute fact, or a necessity or norm or law), which is what it is independently of any finite community's opinion and, pragmatically, depends only on the final opinion destined in a sufficient investigation. That is a destination as far, or near, as the truth itself to you or me or the given finite community. Thus, his theory of inquiry boils down to "Do the science." Those conceptions of truth and the real involve the idea of a community both without definite limits (and thus potentially self-correcting as far as needed) and capable of definite increase of knowledge. [100] As inference, "logic is rooted in the social principle" since it depends on a standpoint that is, in a sense, unlimited. [101]

Paying special attention to the generation of explanations, Peirce outlined the scientific method as coordination of three kinds of inference in a purposeful cycle aimed at settling doubts, as follows (in §III–IV in "A Neglected Argument" [4] except as otherwise noted):

  1. Abduction (or retroduction). Guessing, inference to explanatory hypotheses for selection of those best worth trying. From abduction, Peirce distinguishes induction as inferring, based on tests, the proportion of truth in the hypothesis. Every inquiry, whether into ideas, brute facts, or norms and laws, arises from surprising observations in one or more of those realms (and for example at any stage of an inquiry already underway). All explanatory content of theories comes from abduction, which guesses a new or outside idea to account in a simple, economical way for a surprising or complicative phenomenon. Oftenest, even a well-prepared mind guesses wrong. But the modicum of success of our guesses far exceeds that of sheer luck and seems born of attunement to nature by instincts developed or inherent, especially insofar as best guesses are optimally plausible and simple in the sense, said Peirce, of the "facile and natural", as by Galileo's natural light of reason and as distinct from "logical simplicity". Abduction is the most fertile but least secure mode of inference. Its general rationale is inductive: it succeeds often enough and, without it, there is no hope of sufficiently expediting inquiry (often multi-generational) toward new truths. [102] Coordinative method leads from abducing a plausible hypothesis to judging it for its testability[103] and for how its trial would economize inquiry itself. [104] Peirce calls his pragmatism "the logic of abduction". [105] His pragmatic maxim is: "Consider what effects that might conceivably have practical bearings you conceive the objects of your conception to have. Then, your conception of those effects is the whole of your conception of the object". [99] His pragmatism is a method of reducing conceptual confusions fruitfully by equating the meaning of any conception with the conceivable practical implications of its object's conceived effects – a method of experimentational mental reflection hospitable to forming hypotheses and conducive to testing them. It favors efficiency. The hypothesis, being insecure, needs to have practical implications leading at least to mental tests and, in science, lending themselves to scientific tests. A simple but unlikely guess, if uncostly to test for falsity, may belong first in line for testing. A guess is intrinsically worth testing if it has instinctive plausibility or reasoned objective probability, while subjective likelihood, though reasoned, can be misleadingly seductive. Guesses can be chosen for trial strategically, for their caution (for which Peirce gave as an example the game of Twenty Questions), breadth, and incomplexity. [106] One can hope to discover only that which time would reveal through a learner's sufficient experience anyway, so the point is to expedite it the economy of research is what demands the leap, so to speak, of abduction and governs its art. [104]
  2. Deduction. Two stages:
    1. Explication. Unclearly premised, but deductive, analysis of the hypothesis in order to render its parts as clear as possible.
    2. Demonstration: Deductive argumentation, Euclidean in procedure. Explicit deduction of hypothesis's consequences as predictions, for induction to test, about evidence to be found. Corollarial or, if needed, theorematic.
    1. Classification. Unclearly premised, but inductive, classing of objects of experience under general ideas.
    2. Probation: direct inductive argumentation. Crude (the enumeration of instances) or gradual (new estimate of the proportion of truth in the hypothesis after each test). Gradual induction is qualitative or quantitative if qualitative, then dependent on weightings of qualities or characters [108] if quantitative, then dependent on measurements, or on statistics, or on countings.
    3. Sentential Induction. ". which, by inductive reasonings, appraises the different probations singly, then their combinations, then makes self-appraisal of these very appraisals themselves, and passes final judgment on the whole result".

    Invariant explanation

    In a 2009 TED talk, Deutsch expounded a criterion for scientific explanation, which is to formulate invariants: "State an explanation [publicly, so that it can be dated and verified by others later] that remains invariant [in the face of apparent change, new information, or unexpected conditions]". [109]

    "A bad explanation is easy to vary." [109] : minute 11:22 "The search for hard-to-vary explanations is the origin of all progress" [109] : minute 15:05 "That the truth consists of hard-to-vary assertions about reality is the most important fact about the physical world." [109] : minute 16:15

    Invariance as a fundamental aspect of a scientific account of reality had long been part of philosophy of science: for example, Friedel Weinert's book The Scientist as Philosopher (2004) noted the presence of the theme in many writings from the turn of the 20th century onward, such as works by Henri Poincaré (1902), Ernst Cassirer (1920), Max Born (1949 and 1953), Paul Dirac (1958), Olivier Costa de Beauregard (1966), Eugene Wigner (1967), Lawrence Sklar (1974), Michael Friedman (1983), John D. Norton (1992), Nicholas Maxwell (1993), Alan Cook (1994), Alistair Cameron Crombie (1994), Margaret Morrison (1995), Richard Feynman (1997), Robert Nozick (2001), and Tim Maudlin (2002). [110]

    Science applied to complex systems can involve elements such as transdisciplinarity, systems theory and scientific modelling. The Santa Fe Institute studies such systems [111] Murray Gell-Mann interconnects these topics with message passing. [112]

    In general, the scientific method may be difficult to apply stringently to diverse, interconnected systems and large data sets. In particular, practices used within Big data, such as predictive analytics, may be considered to be at odds with the scientific method. [113]

    Frequently the scientific method is employed not only by a single person but also by several people cooperating directly or indirectly. Such cooperation can be regarded as an important element of a scientific community. Various standards of scientific methodology are used within such an environment.

    Peer review evaluation

    Scientific journals use a process of peer review, in which scientists' manuscripts are submitted by editors of scientific journals to (usually one to three, and usually anonymous) fellow scientists familiar with the field for evaluation. In certain journals, the journal itself selects the referees while in others (especially journals that are extremely specialized), the manuscript author might recommend referees. The referees may or may not recommend publication, or they might recommend publication with suggested modifications, or sometimes, publication in another journal. This standard is practiced to various degrees by different journals and can have the effect of keeping the literature free of obvious errors and generally improve the quality of the material, especially in the journals that use the standard most rigorously. The peer-review process can have limitations when considering research outside the conventional scientific paradigm: problems of "groupthink" can interfere with open and fair deliberation of some new research. [114]

    Documentation and replication

    Sometimes experimenters may make systematic errors during their experiments, veer from standard methods and practices (Pathological science) for various reasons, or, in rare cases, deliberately report false results. Occasionally because of this then, other scientists might attempt to repeat the experiments to duplicate the results.


    Researchers sometimes practice scientific data archiving, such as in compliance with the policies of government funding agencies and scientific journals. In these cases, detailed records of their experimental procedures, raw data, statistical analyses, and source code can be preserved to provide evidence of the methodology and practice of the procedure and assist in any potential future attempts to reproduce the result. These procedural records may also assist in the conception of new experiments to test the hypothesis, and may prove useful to engineers who might examine the potential practical applications of a discovery.

    Data sharing

    When additional information is needed before a study can be reproduced, the author of the study might be asked to provide it. They might provide it, or if the author refuses to share data, appeals can be made to the journal editors who published the study or to the institution which funded the research.


    Since a scientist can't record everything that took place in an experiment, facts selected for their apparent relevance are reported. This may lead, unavoidably, to problems later if some supposedly irrelevant feature is questioned. For example, Heinrich Hertz did not report the size of the room used to test Maxwell's equations, which later turned out to account for a small deviation in the results. The problem is that parts of the theory itself need to be assumed to select and report the experimental conditions. The observations are hence sometimes described as being 'theory-laden'.

    Analytical philosophy

    Philosophy of science looks at the underpinning logic of the scientific method, at what separates science from non-science, and the ethic that is implicit in science. There are basic assumptions, derived from philosophy by at least one prominent scientist, that form the base of the scientific method – namely, that reality is objective and consistent, that humans have the capacity to perceive reality accurately, and that rational explanations exist for elements of the real world. [115] These assumptions from methodological naturalism form a basis on which science may be grounded. Logical Positivist, empiricist, falsificationist, and other theories have criticized these assumptions and given alternative accounts of the logic of science, but each has also itself been criticized.

    Thomas Kuhn examined the history of science in his The Structure of Scientific Revolutions, and found that the actual method used by scientists differed dramatically from the then-espoused method. His observations of science practice are essentially sociological and do not speak to how science is or can be practiced in other times and other cultures.

    Norwood Russell Hanson, Imre Lakatos and Thomas Kuhn have done extensive work on the "theory-laden" character of observation. Hanson (1958) first coined the term for the idea that all observation is dependent on the conceptual framework of the observer, using the concept of gestalt to show how preconceptions can affect both observation and description. [116] He opens Chapter 1 with a discussion of the Golgi bodies and their initial rejection as an artefact of staining technique, and a discussion of Brahe and Kepler observing the dawn and seeing a "different" sunrise despite the same physiological phenomenon. Kuhn [117] and Feyerabend [118] acknowledge the pioneering significance of his work.

    Kuhn (1961) said the scientist generally has a theory in mind before designing and undertaking experiments to make empirical observations, and that the "route from theory to measurement can almost never be traveled backward". This implies that how theory is tested is dictated by the nature of the theory itself, which led Kuhn (1961, p. 166) to argue that "once it has been adopted by a profession . no theory is recognized to be testable by any quantitative tests that it has not already passed". [119]

    Post-modernism and science wars

    Paul Feyerabend similarly examined the history of science, and was led to deny that science is genuinely a methodological process. In his book Against Method he argues that scientific progress is not the result of applying any particular method. In essence, he says that for any specific method or norm of science, one can find a historic episode where violating it has contributed to the progress of science. Thus, if believers in the scientific method wish to express a single universally valid rule, Feyerabend jokingly suggests, it should be 'anything goes'. [120] Criticisms such as his led to the strong programme, a radical approach to the sociology of science.

    The postmodernist critiques of science have themselves been the subject of intense controversy. This ongoing debate, known as the science wars, is the result of conflicting values and assumptions between the postmodernist and realist camps. Whereas postmodernists assert that scientific knowledge is simply another discourse (note that this term has special meaning in this context) and not representative of any form of fundamental truth, realists in the scientific community maintain that scientific knowledge does reveal real and fundamental truths about reality. Many books have been written by scientists which take on this problem and challenge the assertions of the postmodernists while defending science as a legitimate method of deriving truth. [121]

    Anthropology and sociology

    In anthropology and sociology, following the field research in an academic scientific laboratory by Latour and Woolgar, Karin Knorr Cetina has conducted a comparative study of two scientific fields (namely high energy physics and molecular biology) to conclude that the epistemic practices and reasonings within both scientific communities are different enough to introduce the concept of "epistemic cultures", in contradiction with the idea that a so-called "scientific method" is unique and a unifying concept. [122]

    Role of chance in discovery

    Somewhere between 33% and 50% of all scientific discoveries are estimated to have been stumbled upon, rather than sought out. This may explain why scientists so often express that they were lucky. [123] Louis Pasteur is credited with the famous saying that "Luck favours the prepared mind", but some psychologists have begun to study what it means to be 'prepared for luck' in the scientific context. Research is showing that scientists are taught various heuristics that tend to harness chance and the unexpected. [123] [124] This is what Nassim Nicholas Taleb calls "Anti-fragility" while some systems of investigation are fragile in the face of human error, human bias, and randomness, the scientific method is more than resistant or tough – it actually benefits from such randomness in many ways (it is anti-fragile). Taleb believes that the more anti-fragile the system, the more it will flourish in the real world. [26]

    Psychologist Kevin Dunbar says the process of discovery often starts with researchers finding bugs in their experiments. These unexpected results lead researchers to try to fix what they think is an error in their method. Eventually, the researcher decides the error is too persistent and systematic to be a coincidence. The highly controlled, cautious, and curious aspects of the scientific method are thus what make it well suited for identifying such persistent systematic errors. At this point, the researcher will begin to think of theoretical explanations for the error, often seeking the help of colleagues across different domains of expertise. [123] [124]

    Science is the process of gathering, comparing, and evaluating proposed models against observables. A model can be a simulation, mathematical or chemical formula, or set of proposed steps. Science is like mathematics in that researchers in both disciplines try to distinguish what is known from what is unknown at each stage of discovery. Models, in both science and mathematics, need to be internally consistent and also ought to be falsifiable (capable of disproof). In mathematics, a statement need not yet be proven at such a stage, that statement would be called a conjecture. But when a statement has attained mathematical proof, that statement gains a kind of immortality which is highly prized by mathematicians, and for which some mathematicians devote their lives. [125]

    Mathematical work and scientific work can inspire each other. [126] For example, the technical concept of time arose in science, and timelessness was a hallmark of a mathematical topic. But today, the Poincaré conjecture has been proven using time as a mathematical concept in which objects can flow (see Ricci flow).

    Nevertheless, the connection between mathematics and reality (and so science to the extent it describes reality) remains obscure. Eugene Wigner's paper, The Unreasonable Effectiveness of Mathematics in the Natural Sciences, is a very well-known account of the issue from a Nobel Prize-winning physicist. In fact, some observers (including some well-known mathematicians such as Gregory Chaitin, and others such as Lakoff and Núñez) have suggested that mathematics is the result of practitioner bias and human limitation (including cultural ones), somewhat like the post-modernist view of science.

    George Pólya's work on problem solving, [127] the construction of mathematical proofs, and heuristic [128] [129] show that the mathematical method and the scientific method differ in detail, while nevertheless resembling each other in using iterative or recursive steps.

    In Pólya's view, understanding involves restating unfamiliar definitions in your own words, resorting to geometrical figures, and questioning what we know and do not know already analysis, which Pólya takes from Pappus, [130] involves free and heuristic construction of plausible arguments, working backward from the goal, and devising a plan for constructing the proof synthesis is the strict Euclidean exposition of step-by-step details [131] of the proof review involves reconsidering and re-examining the result and the path taken to it.

    Gauss, when asked how he came about his theorems, once replied "durch planmässiges Tattonieren" (through systematic palpable experimentation). [132]

    Imre Lakatos argued that mathematicians actually use contradiction, criticism, and revision as principles for improving their work. [133] In like manner to science, where truth is sought, but certainty is not found, in Proofs and refutations (1976), what Lakatos tried to establish was that no theorem of informal mathematics is final or perfect. This means that we should not think that a theorem is ultimately true, only that no counterexample has yet been found. Once a counterexample, i.e. an entity contradicting/not explained by the theorem is found, we adjust the theorem, possibly extending the domain of its validity. This is a continuous way our knowledge accumulates, through the logic and process of proofs and refutations. (If axioms are given for a branch of mathematics, however, Lakatos claimed that proofs from those axioms were tautological, i.e. logically true, by rewriting them, as did Poincaré (Proofs and Refutations, 1976).)

    Lakatos proposed an account of mathematical knowledge based on Polya's idea of heuristics. In Proofs and Refutations, Lakatos gave several basic rules for finding proofs and counterexamples to conjectures. He thought that mathematical 'thought experiments' are a valid way to discover mathematical conjectures and proofs. [134]

    Relationship with statistics

    When the scientific method employs statistics as part of its arsenal, there are mathematical and practical issues that can have a deleterious effect on the reliability of the output of scientific methods. This is described in a popular 2005 scientific paper "Why Most Published Research Findings Are False" by John Ioannidis, which is considered foundational to the field of metascience. [135] Much research in metascience seeks to identify poor use of statistics and improve its use.

    The particular points raised are statistical ("The smaller the studies conducted in a scientific field, the less likely the research findings are to be true" and "The greater the flexibility in designs, definitions, outcomes, and analytical modes in a scientific field, the less likely the research findings are to be true.") and economical ("The greater the financial and other interests and prejudices in a scientific field, the less likely the research findings are to be true" and "The hotter a scientific field (with more scientific teams involved), the less likely the research findings are to be true.") Hence: "Most research findings are false for most research designs and for most fields" and "As shown, the majority of modern biomedical research is operating in areas with very low pre- and poststudy probability for true findings." However: "Nevertheless, most new discoveries will continue to stem from hypothesis-generating research with low or very low pre-study odds," which means that *new* discoveries will come from research that, when that research started, had low or very low odds (a low or very low chance) of succeeding. Hence, if the scientific method is used to expand the frontiers of knowledge, research into areas that are outside the mainstream will yield the newest discoveries.


    Recall that a hypothesis is a suggested explanation that can be tested. A hypothesis is NOT the question you are trying to answer – it is what you think the answer to the question will be and why. To solve a problem, several hypotheses may be proposed. For example, one hypothesis might be, “The light won’t turn on because the bulb is burned out.” But there could be other answers to the question, and therefore other hypotheses may be proposed. A second hypothesis might be, “The light won’t turn on because the lamp is unplugged” or “The light won’t turn on because the power is out.” A hypothesis should be based on credible background information. A hypothesis is NOT just a guess (not even an educated one), although it can be based on your prior experience (such as in the example where the light won’t turn on). In general, hypotheses in biology should be based on a credible, referenced source of information.

    A hypothesis must be testable to ensure that it is valid. For example, a hypothesis that depends on what a dog thinks is not testable, because we can’t tell what a dog thinks. It should also be falsifiable, meaning that it can be disproven by experimental results. An example of an unfalsifiable hypothesis is “Red is a better color than blue.” There is no experiment that might show this statement to be false. To test a hypothesis, a researcher will conduct one or more experiments designed to eliminate one or more of the hypotheses. This is important: a hypothesis can be disproven, or eliminated, but it can never be proven. Science does not deal in proofs like mathematics. If an experiment fails to disprove a hypothesis, then that explanation (the hypothesis) is supported as the answer to the question. However, that doesn’t mean that later on, we won’t find a better explanation or design a better experiment that will be found to falsify the first hypothesis and lead to a better one.

    Scientific Method - Biology

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      How the Scientific Method Works

      The scientific method attempts to minimize the influence of bias or prejudice in the experimenter. Even the best-intentioned scientists can't escape bias. It results from personal beliefs, as well as cultural beliefs, which means any human filters information based on his or her own experience. Unfortunately, this filtering process can cause a scientist to prefer one outcome over another. For someone trying to solve a problem around the house, succumbing to these kinds of biases is not such a big deal. But in the scientific community, where results have to be reviewed and duplicated, bias must be avoided at all costs.

      ­T­hat's the job of the scientific method. It provides an objective, standardized approach to conducting experiments and, in doing so, improves their results. By using a standardized approach in their investigations, scientists can feel confident that they will stick to the facts and limit the influence of personal, preconceived notions. Even with such a rigorous methodology in place, some scientists still make mistakes. For example, they can mistake a hypothesis for an explanation of a phenomenon without performing experiments. Or they can fail to accurately account for errors, such as measurement errors. Or they can ignore data that does not support the hypothesis.

      Gregor Mendel (1822-1884), an Austrian priest who studied the inheritance of traits in pea plants and helped pioneer the study of genetics, may have fallen victim to a kind of error known as confirmation bias. Confirmation bias is the tendency to see data that supports a hypothesis while ignoring data that does not. Some argue that Mendel obtained a certain result using a small sample size, then continued collecting and censoring data to make sure his original result was confirmed. Although subsequent experiments have proven Mendel's hypothesis, many people still question his methods of experimentation.

      Most of the time, however, the scientific method works and works well. When a hypothesis or a group of related hypotheses have been confirmed through repeated experimental tests, it may become a theory, which can be thought of as the pot of gold at the end of the scientific method rainbow. Theories are much broader in scope than hypotheses and hold enormous predictive power. The theory of relativity, for example, predicted the existence of black holes long before there was evidence to support the idea. It should be noted, however, that one of the goals of science is not to prove theories right, but to prove them wrong. When this happens, a theory must be modified or discarded altogether.

      Are You and Your Students Science Detectives?

      Science Detectives Training Room is a fun way to teach students from elementary level to college about the scientific method. It is also a great way to build problem solving skills. Based on a popular "room escape" genre of online games, players enter a dark room and must work through a set of problems to escape.

      Once the player escapes from the first room, they encounter a summary of the steps they took to escape and how those steps match the steps of the scientific method. At the end of the game the player can print out the results of their training room exercise for review. If used as an assignment, students can submit the printout to their instructor to show how they performed in the activity.

      The game then connects to a follow-up game, The Case of the Mystery Images, which allows students to practice their new detective skills. They are shown a series of images that they have to make hypotheses about in order to progress through the game. They can also print out their work in this game.

      WWW: The Scientific Method

      Each quarter, CBE—Life Sciences Education calls attention to several Web sites of educational interest to the life science community. The journal does not endorse or guarantee the accuracy of the information at any of the listed sites. If you want to comment on the selections or suggest future inclusions, please send a message to [email protected] The sites listed below were last accessed on 1 December 2005.

      The topic selection of the scientific method for this quarter's column was prompted in part by the recent revision of the K� science education standards by the Kansas State Board of Education on November 8, 2005 ( Figure 1 ).

      Kansas State Board of Education.

      Many have interpreted the November actions of the Kansas State Board of Education as allowing the teaching of “intelligent design” as an alternative to biological evolution. One may download the science standards advocated by the Board from the aforementioned Web site. A portion of their rationale for change is presented below.

      Regarding the scientific theory of biological evolution, the curriculum standards call for students to learn about the best evidence for modern evolutionary theory, but also to learn about areas where scientists are raising scientific criticisms of the theory. These curriculum standards reflect the Board's objective of: 1) to help students understand the full range of scientific views that exist on this topic, 2) to enhance critical thinking and the understanding of the scientific method by encouraging students to study different and opposing scientific evidence, and 3) to ensure that science education in our state is `secular, neutral, and nonideological.'

      As the debate about the actions of the Kansas State Board of Education continues, the role of the scientific method in the process of science requires clarification for many.

      The scientific method is the principal methodology by which biological knowledge is gained and disseminated. As fundamental as the scientific method may be, its historical development is poorly understood, its definition is variable, and its deployment is uneven. Scientific progress may occur without the strictures imposed by the formal application of the scientific method. This report explores Web resources that get at the definition, history, and use of the scientific method.

      A good place to begin this odyssey is with the organization known as Science Service. Science Service, a Washington, DC-based nonprofit organization, is best known as the publisher of Science News and as the organizer of the International Science and Engineering Fair. In its promotion of high school science, Science Service provides a Web page describing the scientific method ( Figure 2 ).

      One may find a carefully worded description of the scientific method consisting of the following steps: problem/purpose, hypothesis, procedure, materials, observation/data/results, analysis, and conclusion. Most would agree that this recounting of the scientific method would be appropriate for a budding young scientist, especially one who is preparing a science fair project.

      Another organization that promotes science education for the K� audience is eMINTS (enhancing Missouri's Instructional Networked Teaching Strategies Figure 3 ).

      This organization developed by three Missouri agencies (University of Missouri, the Missouri Department of Elementary and Secondary Education, and the Missouri Department of Higher Education) advocates the following: 𠇎MINTs changes how teachers teach and students learn. Its instructional model provides a research-based approach to organizing instruction and can be implemented in any subject area at any level.” eMINTS provides a page dealing with the scientific method.

      This eMINTS Scientific Method Web page offers links to very high-quality and traditional material that includes activities such as 𠇍oes Soap Float?” and the Scientific Method scramble. One of the links available is to the Discovery School maintained by Discovery Communications ( Figure 4 ).

      Science Fair Central provides a five-step explanation for the scientific method: research, problem, hypothesis, project experimentation, and project conclusion. The material is derived from Janice VanCleave's Guide to the Best Science Fair Projects, a John Wiley & Sons (New York) publication.

      Each of the three Web sites listed above provides a traditional and generally accepted view of the scientific method, as it would be found in support of classroom activities. Most people agree that to understand science, one must do science. The argument continues that to do science, one must use the scientific method as though it were a form of catechism with heavy emphasis on the steps used by the scientific method. For an example of placing emphasis on the steps to the method, please visit the following Web site ( Figure 5 ):

      Frank Wolfs' introduction to the scientific method.

      Dr. Frank Wolfs in the Department of Physics and Astronomy at the University of Rochester (Rochester, NY) provides a scientific method appendix to the laboratory manuals associated with the introductory college physics courses at Rochester. He, as do many of his science colleagues, states that the scientific method has four steps: 1) observation and description of a phenomenon or group of phenomena 2) formulation of a hypothesis to explain the phenomena (in physics, the hypothesis often takes the form of a causal mechanism or a mathematical relation) 3) use of the hypothesis to predict the existence of other phenomena or to predict quantitatively the results of new observations and 4) performance of experimental tests of the predictions by several independent experimenters and properly performed experiments.

      The laboratory manual for my embryology or histology course could have a similar type of statement. As we lead our students into the forest of doing science, we codify the process as requiring prescribed steps, and, like bread crumbs, these steps are to be followed through the forest. This teaching practice causes people to view science as formulaic and perhaps less of a creative process than it really is. This tendency to make the process pedantic is exemplified by the information at the following Web site ( Figure 6 ):

      Lambert Dolphin's steps in the scientific method.

      Lambert Dolphin of Palo Alto, CA, lays out the scientific method in a flowchart manner. Dolphin also mixes this depiction of scientific methodology with a discussion of personal philosophy and religion.

      Another example of the scientific method being incorporated into a personal philosophy is associated with the following Web site ( Figure 7 ).

      Norman W. Edmund's idea of the scientific method.

      Norman W. Edmund is the founder of the well-known Edmund Scientific (Tonawanda, NY), a mail-order company for science supplies. His company has been sold and incorporated into a new company called Scientifics. Edmund considers the scientific method “the greatest idea of all times.” He defines the scientific method as follows: “The term `the scientific method' represents the general pattern of the types of mental activity stages (usually aided by physical activities) that occur in the master method, which we use to obtain, refine, extend and apply knowledge in all fields.”

      The Science Service and eMINTS' use of the term scientific method would be generally accepted in science education fields. Dolphin and Edmund's use would be problematic for many. And in common practice as represented by the physics laboratory manuals, the scientific method is presented as a rigid process that is followed as though it were a religious doctrine. These practices lead us back to the Kansas Board of Education: “secular, neutral, and nonideological.” At this juncture, it is time to visit Charles Darwin.

      Dr. Ian C. Johnston of the Department of Liberal Studies at Malaspina University-College (Nanaimo, British Columbia, Canada) has prepared a handbook for liberal arts students exploring the history of science. He gives his interpretations into the origins of evolutionary theory and in doing so provides insights into the scientific method ( Figure 8 ).

      Ian C. Johnston's interpretations of the origins of evolutionary theory.

      Darwin's delay in publishing his theory involved factors other than the stormy political climate. For what he was proposing marked a significant departure from conventional English empirical science. At the heart of natural philosophy in England, as we have seen earlier, was an emphasis on observation and experiment. Even though most scientists did not follow precisely the Baconian emphasis on the primary role of empirical observation, nevertheless, they recognized the crucial importance of experimental testing of particular hypotheses.

      This requirement presented Darwin with a grave methodological problem, simply because he was proposing a theory in which direct observation and experiment were clearly impossible, at least in the sense that a biologist could confirm the hypothesis of natural selection by observing it in the action of significantly transforming one species into another. Obviously, the time spans involved and the often minute succession of variations by which one species developed out of a species with quite a different appearance (e.g., reptiles from fish) meant that no direct testing by observation and experiment was possible.

      To meet this difficulty, Darwin developed a new scientific procedure, now known as the hypothetico-deductive method. He first developed a theory, relying upon analogy and deduction to organize a plausible explanation, without direct empirical evidence, and then applied that theory to a wide range of facts, to demonstrate the explanatory power of what he was proposing.

      Johnston reminds us that the scientific method has evolved over a period of time and that the lengthy gap between Darwin's Beagle trip and the publication of the Origin of Species had to do with the limitations in the methodology of doing science at that time. Finding both irony and humor in Darwin contributing to the evolution of the scientific method, we turned to Google (htpp:// to search for a history of the scientific method.

      Michael James has provided an interesting essay on the history of the scientific method the essay is a frequent hit on many search engines ( Figure 9 ).

      Michael James' essay on the history of the scientific method.

      James is a graduate student in the human geography department at the Open University in England. He concludes his essay with the following thought: 𠇏or every individual, science acquires systematic knowledge of the truth and laws of natural or physical phenomena that govern the world. Science classifies by definite rules. To be `scientific' is to agree with, and be well instructed in the principles of science. The manner of proceeding to an end, by orderly means, is `method'. The appearance that the use of scientific method is simply logical can be misleading, there is no more complex question of how we arrive at our thoughts.” It seems James would argue that the flow chart showing the scientific method does not cover the thinking involved in the process.

      The now ubiquitous Wikipedia, the Internet encyclopedia, provides a number of portals into the history of the scientific method ( Figure 10 ).

      Wikipedia's entry on Karl Popper.

      Francis Bacon, a contemporary of Shakespeare, developed a method of scientific reasoning and investigation that was widely adhered to for several centuries. Johnston (above) alludes to Darwin having to deal with the Baconian method. Karl Popper developed the hypothetico-deductive method in the twentieth century and its practice involves falsification of the hypothesis. It is the falsification idea that contributes greatly to today's misunderstanding of what science is, and how the modern version of the scientific method is used. The issue of falsification is also where the Kansas Board of Education enters Dante's Divine Comedy and descends into the inferno. The Board's objective one is “to help students understand the full range of scientific views that exist on this topic.”

      How many science teachers or scientists know of the Vienna Circle of science philosophers of the 1920s? These individuals developed a view of analytical philosophy including logical positivism. Karl Popper led the revolt against logical positivism set forth by the Vienna Circle. How many understand the idea of confirmation holism where a falsification of hypothesis can be undone? Who among the proponents and detractors of evolutionary theory have read Lakatos and Feyerabend's modification of Popperian ideas? The Kansas Board of Education wants “to enhance critical thinking and the understanding of the scientific method.” A place to start is at the intersection of the philosophy of science and the scientific method, and Wikipedia would make a fine first step ( Figure 11 ).

      A comparison of Popper's, Kuhn's, and Feyerabend's ideas about scientific theories.

      The scientific method has evolved. The scientific method also has critics. One place that records criticism is the Web site known as the Science Hobbyist. William J. Beaty, an electrical engineer in the Department of Chemistry at the University of Washington (Seattle, WA) hosts this site. He has a page on the site that is titled “Ten Myths of Science: Reexamining What We Think We Know. ” ( Figure 12 ).

      Ten myths of science: reexamining what we think we know.

      McComas provides an argument that 𠇊 General and Universal Scientific Method Exists” is a myth.

      The notion that a common series of steps is followed by all research scientists must be among the most pervasive myths of science given the appearance of such a list in the introductory chapters of many precollege science texts. This myth has been part of the folklore of school science ever since its proposal by statistician Karl Pearson (1937). The steps listed for the scientific method vary from text to text but usually include, a) define the problem, b) gather background information, c) form a hypothesis, d) make observations, e) test the hypothesis, and f) draw conclusions. Some texts conclude their list of the steps of the scientific method by listing communication of results as the final ingredient.

      One of the reasons for the widespread belief in a general scientific method may be the way in which results are presented for publication in research journals. The standardized style makes it seem that scientists follow a standard research plan. Medawar (1990) reacted to the common style exhibited by research papers by calling the scientific paper a fraud since the final journal report rarely outlines the actual way in which the problem was investigated.

      Philosophers of science who have studied working scientists have shown that no research method is applied universally (Carey, 1994 Gibbs & Lawson, 1992 Chalmers, 1990 Gjertsen, 1989). The notion of a single scientific method is so pervasive it seems certain that many students must be disappointed when they discover that scientists do not have a framed copy of the steps of the scientific method posted high above each laboratory workbench.

      Close inspection will reveal that scientists approach and solve problems with imagination, creativity, prior knowledge and perseverance. These, of course, are the same methods used by all problem-solvers. The lesson to be learned is that science is no different from other human endeavors when puzzles are investigated.

      An unusual place to find a discourse on the scientific method is Dharma-Haven, a site that deals with Tibetan medicine and western science. Dr. Terry Halwes of New Haven, CT, operates the site, and he posts a variety of interesting essays. One of them deals with the myth of the scientific method ( Figure 13 ).

      The myth of the scientific method.

      Halwes argues the following: “The procedure that gets taught as `The Scientific Method' is entirely misleading. Studying what scientists actually do is far more interesting. “The site is extensive and rambling at times however, it does pose interesting observations.

      There is no such unique standard method—scientific progress requires many methods𠅋ut students in introductory science courses are taught that `The Scientific Method' is a straightforward procedure, involving testing hypotheses derived from theories in order to test those theories. The `hypothetico-deductive' schema taught to students was not developed as a method at all: It was intended to be a logical analysis of how scientific theories derive support from evidence, and it was developed in a process that intentionally excluded consideration of the process of discovery in science.

      Another critique of the scientific method may be found at the University of New South Wales. Dr. John A. Schuster of the Department of History and Philosophy of Science provides a Web resource titled The Scientific Revolution: An Introduction to the History and Philosophy of Science ( Figure 14 ).

      The scientific revolution: an introduction to the history and philosophy of science.

      Schuster's Chapter 9 is delightful and needs to be read in its entirety. The following two excerpts give the flavor of his arguments:

      Method is a great story which has a wonderful history of at least 2500 years back to Aristotle, who invented the commonly accepted method story. In the 17th century we have people like Francis Bacon, Galileo, Newton who updated and approved that story. The story of method has a real function in science which unfortunately is not to tell us how science is done. In fact, its job is to mislead us as to how science is done. Method operates like a cultural myth, protecting science and scientists because it allows them to say to nonscientists why they (scientists) are special and why they should be left alone. The myth states that there is a way of doing things in science which people outside of science do not know or cannot properly use. And so, in this century, even though this story has been criticized, there are philosophers and other people who still want to tell us that the scientific method exists. They believe a different version of the scientific method can be designed that is viable, one that at long last is the correct version. In other words, people like me are proved wrong if a good version of method becomes finally available. In the 20th century, a new 20th century method story has emerged. Its author, Sir Karl Popper, the most important philosopher of science of this century, meant to elude and reject everything we have just talked about. Many educated people believe that he succeeded, and that a Popperian version of method works and has actually been the real method of science in all times and places. We shall now see what that new method story involves, what are its undoubted strengths, and why in the end, we probably must conclude that it, like all previous method tales, from Aristotle to Newton, functions only as myth and rhetorical packaging.

      All of the above leads to the third objective of the Kansas Board of Education: “to ensure that science education in our state is `secular, neutral, and nonideological.'” Is the process of science about making choices? This experiment is correct. This experiment is wrong. This conclusion is correct. This conclusion is wrong. Based on these choices, science moves forward. If science education is to be “neutral,” then one cannot make choices. One cannot act on the results of tested hypotheses. To act means that one can no longer be neutral. A definition of ideology is “the ideas and manner of thinking characteristic of a group, social class, or individual.” To have no ideology suggests that the group has no ideas or manner of thinking. One might assume the Kansas Board of Education would like science to have no manner of thinking, no scientific method as it were, for to have a method is an expression of ideology. If scientists agree on a particular natural phenomenon, is it ideological to agree with this “theory” and act upon it?

      Focusing on the scientific method, is it prescriptive or descriptive? Of course, the answer is yes and no. It describes a process by which science can be done. And yet, many valid experiments in science today are not hypothesis driven. If an experiment is not hypothesis driven, is it following the scientific method? Can science be performed only through steps associated with the scientific method? In a sense then, the method is being treated as prescriptive. If science is the baby, is the scientific method the bathwater? If we throw out the bathwater, do we run too great a risk of losing the baby?

      The scientific method is a convenient way to introduce students to the process of science. It is an approximation. As the student matures, how we teach what constitutes the scientific method should mature as well to include less black-and-white and more gray. We trust this brief review of Web resources on the topic of the scientific method will help your students gain a better understanding of the process of science and its relationship to its philosophy.

      The Beginning of Method

      What makes science, science? The details vary tremendously across time, space and field of study. For Aristotle, its foundation was passive observation of nature. In the modern age, it often involves experimentation, too. Besides these, according to the Stanford Encyclopedia of Philosophy , the most common elements are “inductive and deductive reasoning, and the formation and testing of hypotheses and theories.”

      Bacon — often called the “father of empiricism” — thought of these strategies as an intellectual toolset for when our own cognitive abilities fall short. “The unassisted hand and the understanding left to itself possess little power,” he writes in the opening lines of the Novum Organum (“New Organon” — a reference to Aristotle’s logical treatise, the Organon , in which he gave perhaps the first guidelines for scientific inquiry). “Effects are produced by the means of instruments and helps,” Bacon continues, “which the understanding requires no less than the hand.”

      As the microscope and telescope reveal spheres of reality hidden to the naked eye, so scientific method grants us myopic humans a view into the deeper structure of the natural world. This is crucial, since science often deals with objects and processes that are inaccessible, whether physically (the center of the Earth), temporally (the evolution of life) or intellectually (quantum mechanics).

      Apart from his method, Bacon made no major discoveries himself. But a contemporary of his, Galileo Galilei — also sometimes called the “father of science” — put the new method to good use in his famous motion experiments and astronomical observations. Then came science’s next superstar, Isaac Newton, with his monumental laws of motion and gravitation. In the Principia Mathematica , Newton even formulated his own methodological rules, or “ regulae philosophandi ,” for scientific reasoning.

      How do scientists use the scientific method in real life?

      Although the process above sounds pretty rigid, it’s actually quite fluid and adaptable. Some scientists never really conduct true “experiments” and focus on other things instead. Taxonomists, for example, focus on how to best classify organisms. They don’t go through the whole process of hypothesis testing and data analysis for what is very important for writing research papers and term papers often assigned to college and university students. Only professional academic writers who work for research paper writing services use scientific method in writing.

      Without the scientific method, people might make up random explanations to problems with no real data to back it up. Thanks to the scientific method, the sum of human knowledge has grown tremendously and hopefully will continue to improve our lives.


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