An experiment is a procedure carried out to support, refute, or validate a hypothesis. Experiments provide insight into cause-and-effect by demonstrating what outcome occurs when a particular factor is manipulated. Experiments vary greatly in goal and scale, but always rely on repeatable procedure and logical analysis of the results. There also exists natural experimental studies.

A child may carry out basic experiments to understand gravity, while teams of scientists may take years of systematic investigation to advance their understanding of a phenomenon. Experiments and other types of hands-on activities are very important to student learning in the science classroom. Experiments can raise test scores and help a student become more engaged and interested in the material they are learning, especially when used over time.[1] Experiments can vary from personal and informal natural comparisons (e.g. tasting a range of chocolates to find a favorite), to highly controlled (e.g. tests requiring complex apparatus overseen by many scientists that hope to discover information about subatomic particles). Uses of experiments vary considerably between the natural and human sciences.

Experiments typically include controls, which are designed to minimize the effects of variables other than the single independent variable. This increases the reliability of the results, often through a comparison between control measurements and the other measurements. Scientific controls are a part of the scientific method. Ideally, all variables in an experiment are controlled (accounted for by the control measurements) and none are uncontrolled. In such an experiment, if all controls work as expected, it is possible to conclude that the experiment works as intended, and that results are due to the effect of the tested variable.

Mirror baby
Even very young children perform rudimentary experiments to learn about the world and how things work.


In the scientific method, an experiment is an empirical procedure that arbitrates competing models or hypotheses.[2][3] Researchers also use experimentation to test existing theories or new hypotheses to support or disprove them.[3][4]

An experiment usually tests a hypothesis, which is an expectation about how a particular process or phenomenon works. However, an experiment may also aim to answer a "what-if" question, without a specific expectation about what the experiment reveals, or to confirm prior results. If an experiment is carefully conducted, the results usually either support or disprove the hypothesis. According to some philosophies of science, an experiment can never "prove" a hypothesis, it can only add support. On the other hand, an experiment that provides a counterexample can disprove a theory or hypothesis, but a theory can always be salvaged by appropriate ad hoc modifications at the expense of simplicity. An experiment must also control the possible confounding factors—any factors that would mar the accuracy or repeatability of the experiment or the ability to interpret the results. Confounding is commonly eliminated through scientific controls and/or, in randomized experiments, through random assignment.

In engineering and the physical sciences, experiments are a primary component of the scientific method. They are used to test theories and hypotheses about how physical processes work under particular conditions (e.g., whether a particular engineering process can produce a desired chemical compound). Typically, experiments in these fields focus on replication of identical procedures in hopes of producing identical results in each replication. Random assignment is uncommon.

In medicine and the social sciences, the prevalence of experimental research varies widely across disciplines. When used, however, experiments typically follow the form of the clinical trial, where experimental units (usually individual human beings) are randomly assigned to a treatment or control condition where one or more outcomes are assessed.[5] In contrast to norms in the physical sciences, the focus is typically on the average treatment effect (the difference in outcomes between the treatment and control groups) or another test statistic produced by the experiment.[6] A single study typically does not involve replications of the experiment, but separate studies may be aggregated through systematic review and meta-analysis.

There are various differences in experimental practice in each of the branches of science. For example, agricultural research frequently uses randomized experiments (e.g., to test the comparative effectiveness of different fertilizers), while experimental economics often involves experimental tests of theorized human behaviors without relying on random assignment of individuals to treatment and control conditions.


One of the first methodical approaches to experiments in the modern sense is visible in the works of the Arab mathematician and scholar Ibn al-Haytham. He conducted his experiments in the field of optics - going back to optical and mathematical problems in the works of Ptolemy - by controlling his experiments due to factors such as self-criticality, reliance on visible results of the experiments as well as a criticality in terms of earlier results. He counts as one of the first scholars using an inductive-experimental method for achieving results.[7] In his book "Optics" he describes the fundamentally new approach to knowledge and research in an experimental sense:

"We should, that is, recommence the inquiry into its principles and premisses, beginning our investigation with an inspection of the things that exist and a survey of the conditions of visible objects. We should distinguish the properties of particulars, and gather by induction what pertains to the eye when vision takes place and what is found in the manner of sensation to be uniform, unchanging, manifest and not subject to doubt. After which we should ascend in our inquiry and reasonings, gradually and orderly, criticizing premisses and exercising caution in regard to conclusions – our aim in all that we make subject to inspection and review being to employ justice, not to follow prejudice, and to take care in all that we judge and criticize that we seek the truth and not to be swayed by opinion. We may in this way eventually come to the truth that gratifies the heart and gradually and carefully reach the end at which certainty appears; while through criticism and caution we may seize the truth that dispels disagreement and resolves doubtful matters. For all that, we are not free from that human turbidity which is in the nature of man; but we must do our best with what we possess of human power. From God we derive support in all things."[8]

According to his explanation, a strictly controlled test execution with a sensibility for the subjectivity and susceptibility of outcomes due to the nature of man is necessary. Furthermore, a critical view on the results and outcomes of earlier scholars is necessary:

"It is thus the duty of the man who studies the writings of scientists, if learning the truth is his goal, to make himself an enemy of all that he reads, and, applying his mind to the core and margins of its content, attack it from every side. He should also suspect himself as he performs his critical examination of it, so that he may avoid falling into either prejudice or leniency."[9]

Thus, a comparison of earlier results with the experimental results is necessary for an objective experiment - the visible results being more important. In the end, this may mean that an experimental researcher must find enough courage to discard traditional opinions or results, especially if these results are not experimental but results from a logical/ mental derivation. In this process of critical consideration, the man himself should not forget that he tends to subjective opinions - through "prejudices" and "leniency" - and thus has to be critical about his own way of building hypotheses.

Francis Bacon (1561–1626), an English philosopher and scientist active in the 17th century, became an influential supporter of experimental science in the English renaissance. He disagreed with the method of answering scientific questions by deduction - similar to Ibn al-Haytham - and described it as follows: "Having first determined the question according to his will, man then resorts to experience, and bending her to conformity with his placets, leads her about like a captive in a procession."[10] Bacon wanted a method that relied on repeatable observations, or experiments. Notably, he first ordered the scientific method as we understand it today.

There remains simple experience; which, if taken as it comes, is called accident, if sought for, experiment. The true method of experience first lights the candle [hypothesis], and then by means of the candle shows the way [arranges and delimits the experiment]; commencing as it does with experience duly ordered and digested, not bungling or erratic, and from it deducing axioms [theories], and from established axioms again new experiments.[11]:101

In the centuries that followed, people who applied the scientific method in different areas made important advances and discoveries. For example, Galileo Galilei (1564-1642) accurately measured time and experimented to make accurate measurements and conclusions about the speed of a falling body. Antoine Lavoisier (1743-1794), a French chemist, used experiment to describe new areas, such as combustion and biochemistry and to develop the theory of conservation of mass (matter).[12] Louis Pasteur (1822-1895) used the scientific method to disprove the prevailing theory of spontaneous generation and to develop the germ theory of disease.[13] Because of the importance of controlling potentially confounding variables, the use of well-designed laboratory experiments is preferred when possible.

A considerable amount of progress on the design and analysis of experiments occurred in the early 20th century, with contributions from statisticians such as Ronald Fisher (1890-1962), Jerzy Neyman (1894-1981), Oscar Kempthorne (1919-2000), Gertrude Mary Cox (1900-1978), and William Gemmell Cochran (1909-1980), among others.

Types of experiment

Experiments might be categorized according to a number of dimensions, depending upon professional norms and standards in different fields of study. In some disciplines (e.g., psychology or political science), a 'true experiment' is a method of social research in which there are two kinds of variables. The independent variable is manipulated by the experimenter, and the dependent variable is measured. The signifying characteristic of a true experiment is that it randomly allocates the subjects to neutralize experimenter bias, and ensures, over a large number of iterations of the experiment, that it controls for all confounding factors.[14]

Controlled experiments

A controlled experiment often compares the results obtained from experimental samples against control samples, which are practically identical to the experimental sample except for the one aspect whose effect is being tested (the independent variable). A good example would be a drug trial. The sample or group receiving the drug would be the experimental group (treatment group); and the one receiving the placebo or regular treatment would be the control one. In many laboratory experiments it is good practice to have several replicate samples for the test being performed and have both a positive control and a negative control. The results from replicate samples can often be averaged, or if one of the replicates is obviously inconsistent with the results from the other samples, it can be discarded as being the result of an experimental error (some step of the test procedure may have been mistakenly omitted for that sample). Most often, tests are done in duplicate or triplicate. A positive control is a procedure similar to the actual experimental test but is known from previous experience to give a positive result. A negative control is known to give a negative result. The positive control confirms that the basic conditions of the experiment were able to produce a positive result, even if none of the actual experimental samples produce a positive result. The negative control demonstrates the base-line result obtained when a test does not produce a measurable positive result. Most often the value of the negative control is treated as a "background" value to subtract from the test sample results. Sometimes the positive control takes the quadrant of a standard curve.

An example that is often used in teaching laboratories is a controlled protein assay. Students might be given a fluid sample containing an unknown (to the student) amount of protein. It is their job to correctly perform a controlled experiment in which they determine the concentration of protein in the fluid sample (usually called the "unknown sample"). The teaching lab would be equipped with a protein standard solution with a known protein concentration. Students could make several positive control samples containing various dilutions of the protein standard. Negative control samples would contain all of the reagents for the protein assay but no protein. In this example, all samples are performed in duplicate. The assay is a colorimetric assay in which a spectrophotometer can measure the amount of protein in samples by detecting a colored complex formed by the interaction of protein molecules and molecules of an added dye. In the illustration, the results for the diluted test samples can be compared to the results of the standard curve (the blue line in the illustration) to estimate the amount of protein in the unknown sample.

Controlled experiments can be performed when it is difficult to exactly control all the conditions in an experiment. In this case, the experiment begins by creating two or more sample groups that are probabilistically equivalent, which means that measurements of traits should be similar among the groups and that the groups should respond in the same manner if given the same treatment. This equivalency is determined by statistical methods that take into account the amount of variation between individuals and the number of individuals in each group. In fields such as microbiology and chemistry, where there is very little variation between individuals and the group size is easily in the millions, these statistical methods are often bypassed and simply splitting a solution into equal parts is assumed to produce identical sample groups.

Once equivalent groups have been formed, the experimenter tries to treat them identically except for the one variable that he or she wishes to isolate. Human experimentation requires special safeguards against outside variables such as the placebo effect. Such experiments are generally double blind, meaning that neither the volunteer nor the researcher knows which individuals are in the control group or the experimental group until after all of the data have been collected. This ensures that any effects on the volunteer are due to the treatment itself and are not a response to the knowledge that he is being treated.

In human experiments, researchers may give a subject (person) a stimulus that the subject responds to. The goal of the experiment is to measure the response to the stimulus by a test method.

Original map by John Snow showing the clusters of cholera cases in the London epidemic of 1854

In the design of experiments, two or more "treatments" are applied to estimate the difference between the mean responses for the treatments. For example, an experiment on baking bread could estimate the difference in the responses associated with quantitative variables, such as the ratio of water to flour, and with qualitative variables, such as strains of yeast. Experimentation is the step in the scientific method that helps people decide between two or more competing explanations – or hypotheses. These hypotheses suggest reasons to explain a phenomenon, or predict the results of an action. An example might be the hypothesis that "if I release this ball, it will fall to the floor": this suggestion can then be tested by carrying out the experiment of letting go of the ball, and observing the results. Formally, a hypothesis is compared against its opposite or null hypothesis ("if I release this ball, it will not fall to the floor"). The null hypothesis is that there is no explanation or predictive power of the phenomenon through the reasoning that is being investigated. Once hypotheses are defined, an experiment can be carried out and the results analysed to confirm, refute, or define the accuracy of the hypotheses.

Experiments can be also designed to estimate spillover effects onto nearby untreated units.

Natural experiments

The term "experiment" usually implies a controlled experiment, but sometimes controlled experiments are prohibitively difficult or impossible. In this case researchers resort to natural experiments or quasi-experiments.[15] Natural experiments rely solely on observations of the variables of the system under study, rather than manipulation of just one or a few variables as occurs in controlled experiments. To the degree possible, they attempt to collect data for the system in such a way that contribution from all variables can be determined, and where the effects of variation in certain variables remain approximately constant so that the effects of other variables can be discerned. The degree to which this is possible depends on the observed correlation between explanatory variables in the observed data. When these variables are not well correlated, natural experiments can approach the power of controlled experiments. Usually, however, there is some correlation between these variables, which reduces the reliability of natural experiments relative to what could be concluded if a controlled experiment were performed. Also, because natural experiments usually take place in uncontrolled environments, variables from undetected sources are neither measured nor held constant, and these may produce illusory correlations in variables under study.

Much research in several science disciplines, including economics, political science, geology, paleontology, ecology, meteorology, and astronomy, relies on quasi-experiments. For example, in astronomy it is clearly impossible, when testing the hypothesis "Stars are collapsed clouds of hydrogen", to start out with a giant cloud of hydrogen, and then perform the experiment of waiting a few billion years for it to form a star. However, by observing various clouds of hydrogen in various states of collapse, and other implications of the hypothesis (for example, the presence of various spectral emissions from the light of stars), we can collect data we require to support the hypothesis. An early example of this type of experiment was the first verification in the 17th century that light does not travel from place to place instantaneously, but instead has a measurable speed. Observation of the appearance of the moons of Jupiter were slightly delayed when Jupiter was farther from Earth, as opposed to when Jupiter was closer to Earth; and this phenomenon was used to demonstrate that the difference in the time of appearance of the moons was consistent with a measurable speed.

Field experiments

Field experiments are so named to distinguish them from laboratory experiments, which enforce scientific control by testing a hypothesis in the artificial and highly controlled setting of a laboratory. Often used in the social sciences, and especially in economic analyses of education and health interventions, field experiments have the advantage that outcomes are observed in a natural setting rather than in a contrived laboratory environment. For this reason, field experiments are sometimes seen as having higher external validity than laboratory experiments. However, like natural experiments, field experiments suffer from the possibility of contamination: experimental conditions can be controlled with more precision and certainty in the lab. Yet some phenomena (e.g., voter turnout in an election) cannot be easily studied in a laboratory.

Contrast with observational study

The black box model for observation (input and output are observables). When there are a feedback with some observer's control, as illustrated, the observation is also an experiment.

An observational study is used when it is impractical, unethical, cost-prohibitive (or otherwise inefficient) to fit a physical or social system into a laboratory setting, to completely control confounding factors, or to apply random assignment. It can also be used when confounding factors are either limited or known well enough to analyze the data in light of them (though this may be rare when social phenomena are under examination). For an observational science to be valid, the experimenter must know and account for confounding factors. In these situations, observational studies have value because they often suggest hypotheses that can be tested with randomized experiments or by collecting fresh data.

Fundamentally, however, observational studies are not experiments. By definition, observational studies lack the manipulation required for Baconian experiments. In addition, observational studies (e.g., in biological or social systems) often involve variables that are difficult to quantify or control. Observational studies are limited because they lack the statistical properties of randomized experiments. In a randomized experiment, the method of randomization specified in the experimental protocol guides the statistical analysis, which is usually specified also by the experimental protocol.[16] Without a statistical model that reflects an objective randomization, the statistical analysis relies on a subjective model.[16] Inferences from subjective models are unreliable in theory and practice.[17] In fact, there are several cases where carefully conducted observational studies consistently give wrong results, that is, where the results of the observational studies are inconsistent and also differ from the results of experiments. For example, epidemiological studies of colon cancer consistently show beneficial correlations with broccoli consumption, while experiments find no benefit.[18]

A particular problem with observational studies involving human subjects is the great difficulty attaining fair comparisons between treatments (or exposures), because such studies are prone to selection bias, and groups receiving different treatments (exposures) may differ greatly according to their covariates (age, height, weight, medications, exercise, nutritional status, ethnicity, family medical history, etc.). In contrast, randomization implies that for each covariate, the mean for each group is expected to be the same. For any randomized trial, some variation from the mean is expected, of course, but the randomization ensures that the experimental groups have mean values that are close, due to the central limit theorem and Markov's inequality. With inadequate randomization or low sample size, the systematic variation in covariates between the treatment groups (or exposure groups) makes it difficult to separate the effect of the treatment (exposure) from the effects of the other covariates, most of which have not been measured. The mathematical models used to analyze such data must consider each differing covariate (if measured), and results are not meaningful if a covariate is neither randomized nor included in the model.

To avoid conditions that render an experiment far less useful, physicians conducting medical trials – say for U.S. Food and Drug Administration approval – quantify and randomize the covariates that can be identified. Researchers attempt to reduce the biases of observational studies with complicated statistical methods such as propensity score matching methods, which require large populations of subjects and extensive information on covariates. Outcomes are also quantified when possible (bone density, the amount of some cell or substance in the blood, physical strength or endurance, etc.) and not based on a subject's or a professional observer's opinion. In this way, the design of an observational study can render the results more objective and therefore, more convincing.


By placing the distribution of the independent variable(s) under the control of the researcher, an experiment – particularly when it involves human subjects – introduces potential ethical considerations, such as balancing benefit and harm, fairly distributing interventions (e.g., treatments for a disease), and informed consent. For example, in psychology or health care, it is unethical to provide a substandard treatment to patients. Therefore, ethical review boards are supposed to stop clinical trials and other experiments unless a new treatment is believed to offer benefits as good as current best practice.[19] It is also generally unethical (and often illegal) to conduct randomized experiments on the effects of substandard or harmful treatments, such as the effects of ingesting arsenic on human health. To understand the effects of such exposures, scientists sometimes use observational studies to understand the effects of those factors.

Even when experimental research does not directly involve human subjects, it may still present ethical concerns. For example, the nuclear bomb experiments conducted by the Manhattan Project implied the use of nuclear reactions to harm human beings even though the experiments did not directly involve any human subjects.

Experimental method in law

The experimental method can be useful in solving juridical problems.[20]

See also


  1. ^ Stohr-Hunt, Patricia (1996). "An Analysis of Frequency of Hands-on Experience and Science Achievement". Journal of Research in Science Teaching. 33. doi:10.1002/(SICI)1098-2736(199601)33:1<101::AID-TEA6>3.0.CO;2-Z.
  2. ^ Cooperstock, Fred I. (2009). General relativistic dynamics : extending Einstein's legacy throughout the universe (Online-Ausg. ed.). Singapore: World Scientific. p. 12. ISBN 978-981-4271-16-5.
  3. ^ a b Griffith, W. Thomas (2001). The physics of everyday phenomena : a conceptual introduction to physics (3rd ed.). Boston: McGraw-Hill. pp. 3–4. ISBN 0-07-232837-1.
  4. ^ Wilczek, Frank; Devine, Betsy (2006). Fantastic realities : 49 mind journeys and a trip to Stockholm. New Jersey: World Scientific. pp. 61–62. ISBN 978-981-256-649-2.
  5. ^ Holland, Paul W. (December 1986). "Statistics and Causal Inference". Journal of the American Statistical Association. 81 (396): 945. doi:10.2307/2289064. JSTOR 2289064.
  6. ^ Druckman, James N.; Greene, Donald P.; Kuklinski, James H.; Lupia, Arthur, eds. (2011). Cambridge handbook of experimental political science. Cambridge: Cambridge University Press. ISBN 9780521174558.
  7. ^ El-Bizri, Nader (2005). "A Philosophical Perspective on Alhazen's Optics". Arabic Sciences and Philosophy (Cambridge University Press). 15 (2): 189–218.
  8. ^ Ibn al-Haytham, Abu Ali Al-Hasan. Optics. p. 5.
  9. ^ Ibn al-Haytham, Abi Ali Al-Hasan. Dubitationes in Ptolemaeum. p. 3.
  10. ^ "Having first determined the question according to his will, man then resorts to experience, and bending her to conformity with his placets, leads her about like a captive in a procession." Bacon, Francis. Novum Organum, i, 63. Quoted in Durant 2012, p. 170.
  11. ^ Durant, Will (2012). The story of philosophy : the lives and opinions of the great philosophers of the western world (2nd ed.). New York: Simon and Schuster. ISBN 978-0-671-69500-2.
  12. ^ Bell, Madison Smartt (2005). Lavoisier in the Year One: The Birth of a New Science in an Age of Revolution. W. W. Norton & Company. ISBN 9780393051551.
  13. ^ Brock, Thomas D, ed. (1988). Pasteur and Modern Science (New illustrated ed.). Springer. ISBN 9783540501015.
  14. ^ "Types of experiments". Department of Psychology, University of California Davis. Archived from the original on 19 December 2014.
  15. ^ Dunning 2012
  16. ^ a b Hinkelmann, Klaus and Kempthorne, Oscar (2008). Design and Analysis of Experiments, Volume I: Introduction to Experimental Design (Second ed.). Wiley. ISBN 978-0-471-72756-9.CS1 maint: Multiple names: authors list (link)
  17. ^ Freedman, David; Pisani, Robert; Purves, Roger (2007). Statistics (4th ed.). New York: Norton. ISBN 978-0-393-92972-0.
  18. ^ Freedman, David A. (2009). Statistical models : theory and practice (Revised ed.). Cambridge: Cambridge University Press. ISBN 978-0-521-74385-3.
  19. ^ Bailey, R.A. (2008). Design of comparative experiments. Cambridge: Cambridge University Press. ISBN 9780521683579.
  20. ^ Zippelius, von Reinhold (1991). Die experimentierende Methode im Recht. Stuttgart: Steiner. ISBN 978-3515059015.

Further reading

  • Dunning, Thad (2012). Natural experiments in the social sciences : a design-based approach. Cambridge: Cambridge University Press. ISBN 978-1107698000.
  • Shadish, William R.; Cook, Thomas D.; Campbell, Donald T. (2002). Experimental and quasi-experimental designs for generalized causal inference (Nachdr. ed.). Boston: Houghton Mifflin. ISBN 0-395-61556-9. (Excerpts)
  • Jeremy, Teigen (2014). "Experimental Methods in Military and Veteran Studies". In Soeters, Joseph; Shields, Patricia; Rietjens, Sebastiaan. Routledge Handbook of Research Methods in Military Studies. New York: Routledge. pp. 228–238.

External links

Blinded experiment

A blind or blinded-experiment is an experiment in which information about the test is masked (kept) from the participant, to reduce or eliminate bias, until after a trial outcome is known. It is understood that bias may be unintentional or subconscious, thus no dishonesty is implied by blinding. If both tester and subject are blinded, the trial is called a double-blind experiment.

Blind testing is used wherever items are to be compared without influences from testers' preferences or expectations, for example in clinical trials to evaluate the effectiveness of medicinal drugs and procedures without placebo effect, observer bias, or conscious deception; and comparative testing of commercial products to objectively assess user preferences without being influenced by branding and other properties not being tested.

Blinding can be imposed on researchers, technicians, or subjects. The opposite of a blind trial is an open trial. Blind experiments are an important tool of the scientific method, in many fields of research—medicine, psychology and the social sciences, natural sciences such as physics and biology, applied sciences such as market research, and many others. In some disciplines, such as medicinal drug testing, blind experiments are considered essential.

In some cases, while blind experiments would be useful, they are impractical or unethical; an example is in the field of developmental psychology: although it would be informative to raise children under arbitrary experimental conditions, such as on a remote island with a fabricated enculturation, it is a violation of ethics and human rights.

The terms blind (adjective) or to blind (transitive verb) when used in this sense are figurative extensions of the literal idea of blindfolding someone. The terms masked or to mask may be used for the same concept; this is commonly the case in ophthalmology, where the word 'blind' is often used in the literal sense.

Some argue that the use of the term "blind" for academic review or experiments is offensive and prefer the alternative term "masked" or "anonymous".

Design of experiments

The design of experiments (DOE, DOX, or experimental design) is the design of any task that aims to describe or explain the variation of information under conditions that are hypothesized to reflect the variation. The term is generally associated with experiments in which the design introduces conditions that directly affect the variation, but may also refer to the design of quasi-experiments, in which natural conditions that influence the variation are selected for observation.

In its simplest form, an experiment aims at predicting the outcome by introducing a change of the preconditions, which is represented by one or more independent variables, also referred to as "input variables" or "predictor variables." The change in one or more independent variables is generally hypothesized to result in a change in one or more dependent variables, also referred to as "output variables" or "response variables." The experimental design may also identify control variables that must be held constant to prevent external factors from affecting the results. Experimental design involves not only the selection of suitable independent, dependent, and control variables, but planning the delivery of the experiment under statistically optimal conditions given the constraints of available resources. There are multiple approaches for determining the set of design points (unique combinations of the settings of the independent variables) to be used in the experiment.

Main concerns in experimental design include the establishment of validity, reliability, and replicability. For example, these concerns can be partially addressed by carefully choosing the independent variable, reducing the risk of measurement error, and ensuring that the documentation of the method is sufficiently detailed. Related concerns include achieving appropriate levels of statistical power and sensitivity.

Correctly designed experiments advance knowledge in the natural and social sciences and engineering. Other applications include marketing and policy making.

Double-slit experiment

In modern physics, the double-slit experiment is a demonstration that light and matter can display characteristics of both classically defined waves and particles; moreover, it displays the fundamentally probabilistic nature of quantum mechanical phenomena. The experiment was first performed with light by Thomas Young in 1801. In 1927, Davisson and Germer demonstrated that electrons show the same behavior, which was later extended to atoms and molecules.Thomas Young's experiment with light was part of classical physics well before quantum mechanics, and the concept of wave-particle duality. He believed it demonstrated that the wave theory of light was correct, and his experiment is sometimes referred to as Young's experiment or Young's slits.

The experiment belongs to a general class of "double path" experiments, in which a wave is split into two separate waves that later combine into a single wave. Changes in the path lengths of both waves result in a phase shift, creating an interference pattern. Another version is the Mach–Zehnder interferometer, which splits the beam with a mirror. In the basic version of this experiment, a coherent light source, such as a laser beam, illuminates a plate pierced by two parallel slits, and the light passing through the slits is observed on a screen behind the plate. The wave nature of light causes the light waves passing through the two slits to interfere, producing bright and dark bands on the screen — a result that would not be expected if light consisted of classical particles. However, the light is always found to be absorbed at the screen at discrete points, as individual particles (not waves), the interference pattern appearing via the varying density of these particle hits on the screen. Furthermore, versions of the experiment that include detectors at the slits find that each detected photon passes through one slit (as would a classical particle), and not through both slits (as would a wave). However, such experiments demonstrate that particles do not form the interference pattern if one detects which slit they pass through. These results demonstrate the principle of wave–particle duality.Other atomic-scale entities, such as electrons, are found to exhibit the same behavior when fired towards a double slit. Additionally, the detection of individual discrete impacts is observed to be inherently probabilistic, which is inexplicable using classical mechanics.The experiment can be done with entities much larger than electrons and photons, although it becomes more difficult as size increases. The largest entities for which the double-slit experiment has been performed were molecules that each comprised 810 atoms (whose total mass was over 10,000 atomic mass units).The double-slit experiment (and its variations) has become a classic thought experiment, for its clarity in expressing the central puzzles of quantum mechanics. Because it demonstrates the fundamental limitation of the ability of the observer to predict experimental results, Richard Feynman called it "a phenomenon which is impossible […] to explain in any classical way, and which has in it the heart of quantum mechanics. In reality, it contains the only mystery [of quantum mechanics]."

Factorial experiment

In statistics, a full factorial experiment is an experiment whose design consists of two or more factors, each with discrete possible values or "levels", and whose experimental units take on all possible combinations of these levels across all such factors. A full factorial design may also be called a fully crossed design. Such an experiment allows the investigator to study the effect of each factor on the response variable, as well as the effects of interactions between factors on the response variable.

For the vast majority of factorial experiments, each factor has only two levels. For example, with two factors each taking two levels, a factorial experiment would have four treatment combinations in total, and is usually called a 2×2 factorial design.

If the number of combinations in a full factorial design is too high to be logistically feasible, a fractional factorial design may be done, in which some of the possible combinations (usually at least half) are omitted.

Harry Harlow

Harry Frederick Harlow (October 31, 1905 – December 6, 1981) was an American psychologist best known for his maternal-separation, dependency needs, and social isolation experiments on rhesus monkeys, which manifested the importance of caregiving and companionship to social and cognitive development. He conducted most of his research at the University of Wisconsin–Madison, where humanistic psychologist Abraham Maslow worked with him for a short period of time.

Harlow's experiments were controversial; they included creating inanimate surrogate mothers for the rhesus infants from wire and wool. Each infant became attached to its particular mother, recognizing its unique face and preferring it above others. Harlow next chose to investigate if the infants had a preference for bare-wire mothers or cloth-covered mothers. For this experiment, he presented the infants with a clothed "mother" and a wire "mother" under two conditions. In one situation, the wire mother held a bottle with food, and the cloth mother held no food. In the other situation, the cloth mother held the bottle, and the wire mother had nothing. Also later in his career, he cultivated infant monkeys in isolation chambers for up to 24 months, from which they emerged intensely disturbed. Some researchers cite the experiments as a factor in the rise of the animal liberation movement in the United States. A Review of General Psychology survey, published in 2002, ranked Harlow as the 26th most cited psychologist of the 20th century.

Large Hadron Collider

The Large Hadron Collider (LHC) is the world's largest and most powerful particle collider and the largest machine in the world. It was built by the European Organization for Nuclear Research (CERN) between 1998 and 2008 in collaboration with over 10,000 scientists and hundreds of universities and laboratories, as well as more than 100 countries. It lies in a tunnel 27 kilometres (17 mi) in circumference and as deep as 175 metres (574 ft) beneath the France–Switzerland border near Geneva.

First collisions were achieved in 2010 at an energy of 3.5 teraelectronvolts (TeV) per beam, about four times the previous world record. After upgrades it reached 6.5 TeV per beam (13 TeV total collision energy, the present world record). At the end of 2018, it entered a two-year shutdown period for further upgrades.

The collider has four crossing points, around which are positioned seven detectors, each designed for certain kinds of research. The LHC primarily collides proton beams, but it can also use beams of heavy ions: Lead–lead collisions and proton-lead collisions are typically done for one month per year. The aim of the LHC's detectors is to allow physicists to test the predictions of different theories of particle physics, including measuring the properties of the Higgs boson and searching for the large family of new particles predicted by supersymmetric theories, as well as other unsolved questions of physics.

Michelson–Morley experiment

The Michelson–Morley experiment was an attempt to detect the existence of aether, a supposed medium permeating space that was thought to be the carrier of light waves. The experiment was performed between April and July 1887 by Albert A. Michelson and Edward W. Morley at what is now Case Western Reserve University in Cleveland, Ohio, and published in November of the same year. It compared the speed of light in perpendicular directions, in an attempt to detect the relative motion of matter through the stationary luminiferous aether ("aether wind"). The result was negative, in that Michelson and Morley found no significant difference between the speed of light in the direction of movement through the presumed aether, and the speed at right angles. This result is generally considered to be the first strong evidence against the then-prevalent aether theory, and initiated a line of research that eventually led to special relativity, which rules out a stationary aether. Of this experiment, Einstein wrote, "If the Michelson-Morley experiment had not brought us into serious embarrassment, no one would have regarded the relativity theory as a (halfway) redemption."Michelson–Morley type experiments have been repeated many times with steadily increasing sensitivity. These include experiments from 1902 to 1905, and a series of experiments in the 1920s. More recent optical resonator experiments confirmed the absence of any aether wind at the 10−17 level. Together with the Ives–Stilwell and Kennedy–Thorndike experiments, Michelson–Morley type experiments form one of the fundamental tests of special relativity theory.

Milgram experiment

The Milgram experiment on obedience to authority figures was a series of social psychology experiments conducted by Yale University psychologist Stanley Milgram. They measured the willingness of study participants, men from a diverse range of occupations with varying levels of education, to obey an authority figure who instructed them to perform acts conflicting with their personal conscience. Participants were led to believe that they were assisting an unrelated experiment, in which they had to administer electric shocks to a "learner." These fake electric shocks gradually increased to levels that would have been fatal had they been real.The experiment found, unexpectedly, that a very high proportion of men would fully obey the instructions, albeit reluctantly. Milgram first described his research in a 1963 article in the Journal of Abnormal and Social Psychology and later discussed his findings in greater depth in his 1974 book, Obedience to Authority: An Experimental View.The experiments began in July 1961, in the basement of Linsly-Chittenden Hall at Yale University, three months after the start of the trial of German Nazi war criminal Adolf Eichmann in Jerusalem. Milgram devised his psychological study to answer the popular contemporary question: "Could it be that Eichmann and his million accomplices in the Holocaust were just following orders? Could we call them all accomplices?" The experiment was repeated many times around the globe, with fairly consistent results.

Miller–Urey experiment

The Miller–Urey experiment (or Miller experiment) was a chemical experiment that simulated the conditions thought at the time to be present on the early Earth, and tested the chemical origin of life under those conditions. The experiment supported Alexander Oparin's and J. B. S. Haldane's hypothesis that putative conditions on the primitive Earth favoured chemical reactions that synthesized more complex organic compounds from simpler inorganic precursors. Considered to be the classic experiment investigating abiogenesis, it was conducted in 1952 by Stanley Miller, with assistance from Harold Urey, at the University of Chicago and later the University of California, San Diego and published the following year.After Miller's death in 2007, scientists examining sealed vials preserved from the original experiments were able to show that there were actually well over 20 different amino acids produced in Miller's original experiments. That is considerably more than what Miller originally reported, and more than the 20 that naturally occur in life. More recent evidence suggests that Earth's original atmosphere might have had a composition different from the gas used in the Miller experiment, but prebiotic experiments continue to produce racemic mixtures of simple to complex compounds under varying conditions.

Philadelphia Experiment

The Philadelphia Experiment is an alleged military experiment supposed to have been carried out by the U.S. Navy at the Philadelphia Naval Shipyard in Philadelphia, Pennsylvania, sometime around October 28, 1943. The U.S. Navy destroyer escort USS Eldridge (DE-173) was claimed to have been rendered invisible (or "cloaked") to enemy devices.

The story first appeared in 1955, in letters of unknown origin sent to a writer and astronomer, Morris K. Jessup. It is widely understood to be a hoax; the U.S. Navy maintains that no such experiment was ever conducted, that the details of the story contradict well-established facts about USS Eldridge, and that the alleged claims do not conform to known physical laws.

Prohibition in the United States

Prohibition in the United States was a nationwide constitutional ban on the production, importation, transportation, and sale of alcoholic beverages from 1920 to 1933.

During the nineteenth century, alcoholism, family violence, and saloon-based political corruption prompted prohibitionists, led by pietistic Protestants, to end the alcoholic beverage trade to cure the ill society and weaken the political opposition. One result was that many communities in the late-nineteenth and early-twentieth centuries introduced alcohol prohibition, with the subsequent enforcement in law becoming a hotly debated issue. Prohibition supporters, called "drys", presented it as a victory for public morals and health.

Promoted by the "dry" crusaders, the movement was led by pietistic Protestants and social Progressives in the Prohibition, Democratic, and Republican parties. It gained a national grass roots base through the Woman's Christian Temperance Union. After 1900, it was coordinated by the Anti-Saloon League. Opposition from the beer industry mobilized "wet" supporters from the Catholic and German Lutheran communities. They had funding to fight back, but by 1917–18 the German community had been marginalized by the nation's war against Germany, and the brewing industry was shut down in state after state by the legislatures and finally nationwide under the Eighteenth Amendment to the United States Constitution in 1920. Enabling legislation, known as the Volstead Act, set down the rules for enforcing the federal ban and defined the types of alcoholic beverages that were prohibited. For example, religious use of wine was allowed. Private ownership and consumption of alcohol were not made illegal under federal law, but local laws were stricter in many areas, with some states banning possession outright.

Criminal gangs were able to gain control of the beer and liquor supply for many cities. By the late-1920s a new opposition mobilized nationwide. Wets attacked prohibition as causing crime, lowering local revenues, and imposing "rural" Protestant religious values on "urban" United States. Prohibition ended with the ratification of the Twenty-first Amendment, which repealed the Eighteenth Amendment on December 5, 1933. Some states continued statewide prohibition, marking one of the last stages of the Progressive Era.

Research shows that prohibition reduced overall alcohol consumption by half during the 1920s, and consumption remained below pre-Prohibition levels until the 1940s, suggesting that Prohibition did socialize a significant proportion of the population in temperate habits, at least temporarily. Rates of liver cirrhosis "fell by 50% early in Prohibition and recovered promptly after Repeal in 1933." Criticism remains that Prohibition led to unintended consequences such as a century of Prohibition-influenced legislation and the growth of urban crime organizations, though some scholars have argued that violent crime did not increase dramatically, while others have argued that crime during the Prohibition era was properly attributed to increased urbanization, rather than the criminalization of alcohol use. As an experiment it lost supporters every year, and lost tax revenue that governments needed when the Great Depression began in 1929.


A quasi-experiment is an empirical interventional study used to estimate the causal impact of an intervention on target population without random assignment. Quasi-experimental research shares similarities with the traditional experimental design or randomized controlled trial, but it specifically lacks the element of random assignment to treatment or control. Instead, quasi-experimental designs typically allow the researcher to control the assignment to the treatment condition, but using some criterion other than random assignment (e.g., an eligibility cutoff mark). In some cases, the researcher may have control over assignment to treatment.

Quasi-experiments are subject to concerns regarding internal validity, because the treatment and control groups may not be comparable at baseline. With random assignment, study participants have the same chance of being assigned to the intervention group or the comparison group. As a result, differences between groups on both observed and unobserved characteristics would be due to chance, rather than to a systematic factor related to treatment (e.g., illness severity). Randomization itself does not guarantee that groups will be equivalent at baseline. Any change in characteristics post-intervention is likely attributable to the intervention. With quasi-experimental studies, it may not be possible to convincingly demonstrate a causal link between the treatment condition and observed outcomes. This is particularly true if there are confounding variables that cannot be controlled or accounted for.

Schrödinger's cat

Schrödinger's cat is a thought experiment, sometimes described as a paradox, devised by Austrian physicist Erwin Schrödinger in 1935. It illustrates what he saw as the problem of the Copenhagen interpretation of quantum mechanics applied to everyday objects. The scenario presents a hypothetical cat that may be simultaneously both alive and dead, a state known as a quantum superposition, as a result of being linked to a random subatomic event that may or may not occur.

The thought experiment is also often featured in theoretical discussions of the interpretations of quantum mechanics. Schrödinger coined the term Verschränkung (entanglement) in the course of developing the thought experiment.

Scientific control

A scientific control is an experiment or observation designed to minimize the effects of variables other than the independent variable. This increases the reliability of the results, often through a comparison between control measurements and the other measurements. Scientific controls are a part of the scientific method.

Stanford prison experiment

The Stanford Prison Experiment (SPE) was a social psychology experiment that attempted to investigate the psychological effects of perceived power, focusing on the struggle between prisoners and prison officers. It was conducted at Stanford University on the days of August 14–20, 1971, by a research group led by psychology professor Philip Zimbardo using college students. In the study, volunteers were randomly assigned to be either "guards" or "prisoners" in a mock prison, with Zimbardo himself serving as the superintendent. Several "prisoners" left mid-experiment, and the whole experiment was abandoned after six days. Early reports on experimental results claimed that students quickly embraced their assigned roles, with some guards enforcing authoritarian measures and ultimately subjecting some prisoners to psychological torture, while many prisoners passively accepted psychological abuse and, by the officers' request, actively harassed other prisoners who tried to stop it. The experiment has been described in many introductory social psychology textbooks, although some have chosen to exclude it because its methodology is sometimes questioned.The U.S. Office of Naval Research funded the experiment as an investigation into the causes of difficulties between guards and prisoners in the United States Navy and United States Marine Corps. Certain portions of it were filmed, and excerpts of footage are publicly available.

Some of the experiment's findings have been called into question, and the experiment has been criticized for unscientific methodology and possible fraud. Critics have noted that Zimbardo instructed the "guards" to exert psychological control over the "prisoners", and that some of the participants behaved in a way that would help the study, so that, as one "guard" later put it, "the researchers would have something to work with." Variants of the experiment have been performed by other researchers, but none of these attempts have replicated the results of the SPE.

Stern–Gerlach experiment

The Stern–Gerlach experiment demonstrated that the spatial orientation of angular momentum is quantized. Thus an atomic-scale system was shown to have intrinsically quantum properties. In the original experiment, silver atoms were sent through a spatially varying magnetic field, which deflected them before they struck a detector screen, such as a glass slide. Particles with non-zero magnetic moment are deflected, due to the magnetic field gradient, from a straight path. The screen reveals discrete points of accumulation, rather than a continuous distribution, owing to their quantized spin. Historically, this experiment was decisive in convincing physicists of the reality of angular-momentum quantization in all atomic-scale systems.The experiment was first conducted by the German physicists Otto Stern and Walter Gerlach in 1922.

Theory of relativity

The theory of relativity usually encompasses two interrelated theories by Albert Einstein: special relativity and general relativity. Special relativity applies to elementary particles and their interactions, describing all their physical phenomena except gravity. General relativity explains the law of gravitation and its relation to other forces of nature. It applies to the cosmological and astrophysical realm, including astronomy.The theory transformed theoretical physics and astronomy during the 20th century, superseding a 200-year-old theory of mechanics created primarily by Isaac Newton. It introduced concepts including spacetime as a unified entity of space and time, relativity of simultaneity, kinematic and gravitational time dilation, and length contraction. In the field of physics, relativity improved the science of elementary particles and their fundamental interactions, along with ushering in the nuclear age. With relativity, cosmology and astrophysics predicted extraordinary astronomical phenomena such as neutron stars, black holes, and gravitational waves.

Thought experiment

A thought experiment (German: Gedankenexperiment, Gedanken-Experiment, or Gedankenerfahrung) considers some hypothesis, theory, or principle for the purpose of thinking through its consequences. Given the structure of the experiment, it may not be possible to perform it, and even if it could be performed, there need not be an intention to perform it.

The common goal of a thought experiment is to explore the potential consequences of the principle in question:

"A thought experiment is a device with which one performs an intentional, structured process of intellectual deliberation in order to speculate, within a specifiable problem domain, about potential consequents (or antecedents) for a designated antecedent (or consequent)" (Yeates, 2004, p. 150).Examples of thought experiments include Schrödinger's cat, illustrating quantum indeterminacy through the manipulation of a perfectly sealed environment and a tiny bit of radioactive substance, and Maxwell's demon, which attempts to demonstrate the ability of a hypothetical finite being to violate the 2nd law of thermodynamics.

Tuskegee syphilis experiment

The Tuskegee Study of Untreated Syphilis in the Negro Male was an infamous and unethical clinical study conducted between 1932 and 1972 by the U.S. Public Health Service. The purpose of this study was to observe the natural history of untreated syphilis; the African-American men in the study were told they were receiving free health care from the United States government.The Public Health Service started working on this study in 1932 in collaboration with Tuskegee University, a historically black college in Alabama. Investigators enrolled in the study a total of 600 impoverished, African-American sharecroppers from Macon County, Alabama. Of these men, 399 had previously contracted syphilis before the study began, and 201 did not have the disease. The men were given free medical care, meals, and free burial insurance for participating in the study. The men were told that the study was only going to last six months, but it actually lasted 40 years. After funding for treatment was lost, the study was continued without informing the men that they would never be treated. None of the men were told that they had the disease, and none were treated with penicillin even after the antibiotic was proven to successfully treat syphilis. According to the Centers for Disease Control, the men were told that they were being treated for "bad blood", a colloquialism that described various conditions such as syphilis, anemia, and fatigue. "Bad blood"—specifically the collection of illnesses the term included—was a leading cause of death within the southern African-American community.The 40-year study was controversial for reasons related to ethical standards. Researchers knowingly failed to treat patients appropriately after the 1940s validation of penicillin was found as an effective cure for the disease that they were studying. The revelation in 1972 of study failures by a whistleblower, Peter Buxtun, led to major changes in U.S. law and regulation on the protection of participants in clinical studies. Now studies require informed consent, communication of diagnosis, and accurate reporting of test results.By 1947, penicillin had become the standard treatment for syphilis. Choices available to the doctors involved in the study might have included treating all syphilitic subjects and closing the study, or splitting off a control group for testing with penicillin. Instead, the Tuskegee scientists continued the study without treating any participants; they withheld penicillin and information about it from the patients. In addition, scientists prevented participants from accessing syphilis treatment programs available to other residents in the area. The study continued, under numerous US Public Health Service supervisors, until 1972, when a leak to the press resulted in its termination on November 16 of that year. The victims of the study, all African American, included numerous men who died of syphilis, 40 wives who contracted the disease, and 19 children born with congenital syphilis.

The Tuskegee Syphilis Study, cited as "arguably the most infamous biomedical research study in U.S. history", led to the 1979 Belmont Report and to the establishment of the Office for Human Research Protections (OHRP). It also led to federal laws and regulations requiring Institutional Review Boards for the protection of human subjects in studies involving them. The OHRP manages this responsibility within the US Department of Health and Human Services (HHS).On May 16, 1997, President Bill Clinton formally apologized on behalf of the United States to victims of the experiment.

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