What should an experiment have

Ever vaster amounts of data have been produced by particle colliders as they have grown from room-size apparata, to tens of kilometers long mega-labs. Vast numbers of background interactions that are well understood and theoretically uninteresting occur in the detector. These have to be combed in order to identify interactions of potential interest. Protons that collide in the LHC and similar hadron colliders are composed of more elementary particles, collectively labeled partons.

Partons mutually interact, exponentially increasing the number of background interactions. In fact, a minuscule number of interactions are selected from the overwhelming number that occur in the detector.

In contrast, lepton collisions, such as collisions of electrons and positrons, produce much lower backgrounds, since leptons are not composed of more elementary particles. Thus, a successful search for new elementary particles critically depends on successfully crafting selection criteria and techniques at the stage of data collection and at the stage of data analysis. But gradual development and changes in data selection procedures in the colliders raises an important epistemological concern.

In other words, how does one decide which interactions to detect and analyze in a multitude, in order to minimize the possibility of throwing out novel and unexplored ones? One way of searching through vast amounts of data that are already in, i.

Physicists employ the technique of data cuts in such analysis. They cut out data that may be unreliable—when, for instance, a data set may be an artefact rather than a genuine particle interaction the experimenters expect. Thus, if under various data cuts a result remains stable, then it is increasingly likely to be correct and to represent the genuine phenomenon the physicists think it represents.

The robustness of the result under various data cuts minimizes the possibility that the detected phenomenon only mimics the genuine one Franklin , —5. At the data-acquisition stage, however, this strategy does not seem applicable. As Panofsky suggests, one does not know with certainty which of the vast number of the events in the detector may be of interest. Yet, Karaca [ 13 ] argues that a form of robustness is in play even at the acquisition stage.

This experimental approach amalgamates theoretical expectations and empirical results, as the example of the hypothesis of specific heavy particles is supposed to illustrate. Along with the Standard Model of particle physics, a number of alternative models have been proposed.

Their predictions of how elementary particles should behave often differ substantially. Yet in contrast to the Standard Model, they all share the hypothesis that there exist heavy particles that decay into particles with high transverse momentum. Physicists apply a robustness analysis in testing this hypothesis, the argument goes. First, they check whether the apparatus can detect known particles similar to those predicted. Second, guided by the hypothesis, they establish various trigger algorithms.

They are necessary because the frequency and the number of interactions far exceed the limited recording capacity. And, finally, they observe whether any results remain stable across the triggers. And one way around this problem is for physicists to produce as many alternative models as possible, including those that may even seem implausible at the time.

Perovic suggests that such a potential failure, namely to spot potentially relevant events occurring in the detector, may be also a consequence of the gradual automation of the detection process. The early days of experimentation in particle physics, around WWII, saw the direct involvement of the experimenters in the process.

Experimental particle physics was a decentralized discipline where experimenters running individual labs had full control over the triggers and analysis. The experimenters could also control the goals and the design of experiments. Fixed target accelerators, where the beam hits the detector instead of another beam, produced a number of particle interactions that was manageable for such labs.

The chance of missing an anomalous event not predicted by the current theory was not a major concern in such an environment. Yet such labs could process a comparatively small amount of data. This has gradually become an obstacle, with the advent of hadron colliders. They work at ever-higher energies and produce an ever-vaster number of background interactions.

That is why the experimental process has become increasingly automated and much more indirect. Trained technicians instead of experimenters themselves at some point started to scan the recordings.

Eventually, these human scanners were replaced by computers, and a full automation of detection in hadron colliders has enabled the processing of vast number of interactions. This was the first significant change in the transition from small individual labs to mega-labs. The second significant change concerned the organization and goals of the labs.

The mega-detectors and the amounts of data they produced required exponentially more staff and scientists. This in turn led to even more centralized and hierarchical labs and even longer periods of design and performance of the experiments.

As a result, focusing on confirming existing dominant hypotheses rather than on exploratory particle searches was the least risky way of achieving results that would justify unprecedented investments. Now, an indirect detection process combined with mostly confirmatory goals is conducive to overlooking of unexpected interactions. As such, it may impede potentially crucial theoretical advances stemming from missed interactions.

This possibility that physicists such as Panofsky have acknowledged is not a mere speculation. In fact, the use of semi-automated, rather than fully-automated regimes of detection turned out to be essential for a number of surprising discoveries that led to theoretical breakthroughs. In the experiments, physicists were able to perform exploratory detection and visual analysis of practically individual interactions due to low number of background interactions in the linear electron-positron collider.

And they could afford to do this in an energy range that the existing theory did not recognize as significant, which led to them making the discovery. None of this could have been done in the fully automated detecting regime of hadron colliders that are indispensable when dealing with an environment that contains huge numbers of background interactions.

And in some cases, such as the Fermilab experiments that aimed to discover weak neutral currents, an automated and confirmatory regime of data analysis contributed to the failure to detect particles that were readily produced in the apparatus. The complexity of the discovery process in particle physics does not end with concerns about what exact data should be chosen out of the sea of interactions.

The so-called look-elsewhere effect results in a tantalizing dilemma at the stage of data analysis. Suppose that our theory tells us that we will find a particle in an energy range. And suppose we find a significant signal in a section of that very range. Perhaps we should keep looking elsewhere within the range to make sure it is not another particle altogether we have discovered. It may be a particle that left other undetected traces in the range that our theory does not predict, along with the trace we found.

The question is to what extent we should look elsewhere before we reach a satisfying level of certainty that it is the predicted particle we have discovered. The Higgs boson is a particle responsible for the mass of other particles. This pull, which we call mass, is different for different particles.

It is predicted by the Standard Model, whereas alternative models predict somewhat similar Higgs-like particles. A prediction based on the Standard Model tells us with high probability that we will find the Higgs particle in a particular range.

Yet a simple and an inevitable fact of finding it in a particular section of that range may prompt us to doubt whether we have truly found the exact particle our theory predicted. Our initial excitement may vanish when we realize that we are much more likely to find a particle of any sort—not just the predicted particle—within the entire range than in a particular section of that range. In fact, the likelihood of us finding it in a particular bin of the range is about hundred times lower.

In other words, the fact that we will inevitably find the particle in a particular bin, not only in a particular range, decreases the certainty that it was the Higgs we found. Given this fact alone we should keep looking elsewhere for other possible traces in the range once we find a significant signal in a bin. We should not proclaim the discovery of a particle predicted by the Standard Model or any model for that matter too soon.

But for how long should we keep looking elsewhere? And what level of certainty do we need to achieve before we proclaim discovery? The answer boils down to the weight one gives the theory and its predictions. Theoreticians were confident that a finding within the range any of eighty bins that was of standard reliability of three or four sigma , coupled with the theoretical expectations that Higgs would be found, would be sufficient.

In contrast, experimentalists argued that at no point of data analysis should the pertinence of the look-elsewhere effect be reduced, and the search proclaimed successful, with the help of the theoretical expectations concerning Higgs.

One needs to be as careful in combing the range as one practically may. This is a standard under which very few findings have turned out to be a fluctuation in the past. Dawid argues that a question of an appropriate statistical analysis of data is at the heart of the dispute. The reasoning of the experimentalists relied on a frequentist approach that does not specify the probability of the tested hypothesis. It actually isolates statistical analysis of data from the prior probabilities.

The theoreticians, however, relied on Bayesian analysis. It starts with prior probabilities of initial assumptions and ends with the assessment of the probability of tested hypothesis based on the collected evidence. The prior expectations that the theoreticians had included in their analysis had already been empirically corroborated by previous experiments after all.

Experiment can also provide us with evidence for the existence of the entities involved in our theories. For details of this episode see Appendix 7. Experiment can also help to articulate a theory.

For details of this episode see Appendix 8. One comment that has been made concerning the philosophy of experiment is that all of the examples are taken from physics and are therefore limited.

In this section arguments will be presented that these discussions also apply to biology. Although all of the illustrations of the epistemology of experiment come from physics, David Rudge ; has shown that they are also used in biology.

The typical form of the moth has a pale speckled appearance and there are two darker forms, f. The typical form of the moth was most prevalent in the British Isles and Europe until the middle of the nineteenth century.

At that time things began to change. Increasing industrial pollution had both darkened the surfaces of trees and rocks and had also killed the lichen cover of the forests downwind of pollution sources.

Coincident with these changes, naturalists had found that rare, darker forms of several moth species, in particular the Peppered Moth, had become common in areas downwind of pollution sources. Kettlewell attempted to test a selectionist explanation of this phenomenon. Ford ; had suggested a two-part explanation of this effect: 1 darker moths had a superior physiology and 2 the spread of the melanic gene was confined to industrial areas because the darker color made carbonaria more conspicuous to avian predators in rural areas and less conspicuous in polluted areas.

Kettlewell believed that Ford had established the superior viability of darker moths and he wanted to test the hypothesis that the darker form of the moth was less conspicuous to predators in industrial areas. In the first part he used human observers to investigate whether his proposed scoring method would be accurate in assessing the relative conspicuousness of different types of moths against different backgrounds.

The second step involved releasing birds into a cage containing all three types of moth and both soot-blackened and lichen covered pieces of bark as resting places. After some difficulties see Rudge for details , Kettlewell found that birds prey on moths in an order of conspicuousness similar to that gauged by human observers. The third step was to investigate whether birds preferentially prey on conspicuous moths in the wild.

Kettlewell used a mark-release-recapture experiment in both a polluted environment Birmingham and later in an unpolluted wood. He released marked male moths of all three types in an area near Birmingham, which contained predators and natural boundaries. He then recaptured the moths using two different types of trap, each containing virgin females of all three types to guard against the possibility of pheromone differences. Kettlewell found that carbonaria was twice as likely to survive in soot-darkened environments He worried, however, that his results might be an artifact of his experimental procedures.

Perhaps the traps used were more attractive to one type of moth, that one form of moth was more likely to migrate, or that one type of moth just lived longer. He eliminated the first alternative by showing that the recapture rates were the same for both types of trap.

The use of natural boundaries and traps placed beyond those boundaries eliminated the second, and previous experiments had shown no differences in longevity. Further experiments in polluted environments confirmed that carbonaria was twice as likely to survive as typical. An experiment in an unpolluted environment showed that typical was three times as likely to survive as carbonaria. Kettlewell concluded that such selection was the cause of the prevalence of carbonaria in polluted environments.

Rudge also demonstrates that the strategies used by Kettlewell are those described above in the epistemology of experiment. His examples are given in Table 1. For more details see Rudge Table 1. Examples of epistemological strategies used by experimentalists in evolutionary biology, from H.

See Rudge The roles that experiment plays in physics are also those it plays in biology. I discussed earlier a set of crucial experiments that decided between two competing classes of theories, those that conserved parity and those that did not.

In this section I will discuss an experiment that decided among three competing mechanisms for the replication of DNA, the molecule now believed to be responsible for heredity. This is another crucial experiment. It strongly supported one proposed mechanism and argued against the other two. For details of this episode see Holmes Their proposed structure consisted of two polynucleotide chains helically wound about a common axis.

The chains were bound together by combinations of four nitrogen bases — adenine, thymine, cytosine, and guanine. Because of structural requirements only the base pairs adenine-thymine and cytosine-guanine are allowed.

Each chain is thus complementary to the other. If there is an adenine base at a location in one chain there is a thymine base at the same location on the other chain, and vice versa. The same applies to cytosine and guanine.

The order of the bases along a chain is not, however, restricted in any way, and it is the precise sequence of bases that carries the genetic information. The significance of the proposed structure was not lost on Watson and Crick when they made their suggestion. If DNA was to play this crucial role in genetics, then there must be a mechanism for the replication of the molecule. Within a short period of time following the Watson-Crick suggestion, three different mechanisms for the replication of the DNA molecule were proposed Delbruck and Stent These are illustrated in Figure A.

The first, proposed by Gunther Stent and known as conservative replication, suggested that each of the two strands of the parent DNA molecule is replicated in new material.

This yields a first generation which consists of the original parent DNA molecule and one newly-synthesized DNA molecule. Left Conservative replication.

Center Semiconservative replication. Right Dispersive replication. The parent chains break at intervals, and the parental segments combine with new segments to form the daughter chains. From Lehninger The second proposed mechanism, known as semiconservative replication is when each strand of the parental DNA acts as a template for a second newly-synthesized complementary strand, which then combines with the original strand to form a DNA molecule.

This was proposed by Watson and Crick b. The first generation consists of two hybrid molecules, each of which contains one strand of parental DNA and one newly synthesized strand. The second generation consists of two hybrid molecules and two totally new DNAs.

The third mechanism, proposed by Max Delbruck, was dispersive replication, in which the parental DNA chains break at intervals and the parental segments combine with new segments to form the daughter strands.

Meselson and Stahl described their proposed method. To this end a method was developed for the detection of small density differences among macromolecules.

Figure B: Schematic representation of the Meselson-Stahl experiment. From Watson The experiment is described schematically in Figure B. Meselson and Stahl placed a sample of DNA in a solution of cesium chloride.

As the sample is rotated at high speed the denser material travels further away from the axis of rotation than does the less dense material. This results in a solution of cesium chloride that has increasing density as one goes further away from the axis of rotation. The DNA reaches equilibrium at the position where its density equals that of the solution. Meselson and Stahl grew E.

They first showed that they could indeed separate the two different mass molecules of DNA by centrifugation Figure C. The separation of the two types of DNA is clear in both the photograph obtained by absorbing ultraviolet light and in the graph showing the intensity of the signal, obtained with a densitometer.

In addition, the separation between the two peaks suggested that they would be able to distinguish an intermediate band composed of hybrid DNA from the heavy and light bands. These early results argued both that the experimental apparatus was working properly and that all of the results obtained were correct. It is difficult to imagine either an apparatus malfunction or a source of experimental background that could reproduce those results. In both of those episodes it was the results themselves that argued for their correctness.

From Meselson and Stahl The cell membranes were broken to release the DNA into the solution and the samples were centrifuged and ultraviolet absorption photographs taken. In addition, the photographs were scanned with a recording densitometer. The results are shown in Figure D, showing both the photographs and the densitometer traces. The figure shows that one starts only with heavy fully-labeled DNA.

As time proceeds one sees more and more half-labeled DNA, until at one generation time only half-labeled DNA is present. This is exactly what the semiconservative replication mechanism predicts. By four generations the sample consists almost entirely of unlabeled DNA.

A test of the conclusion that the DNA in the intermediate density band was half labeled was provided by examination of a sample containing equal amounts of generations 0 and 1. If the semiconservative mechanism is correct then Generation 1.

This is precisely what one would expect if that DNA were half labeled. Right Densitometer traces of the photographs. As time proceeds a second intermediate band begins to appear until at one generation all of the sample is of intermediate mass Hybrid DNA. At longer times a band of light DNA appears, until at 4. This is exactly what is predicted by the Watson-Crick semiconservative mechanism. Meselson and Stahl also noted the implications of their work for deciding among the proposed mechanisms for DNA replication.

According to this idea, the two chains separate, exposing the hydrogen-bonding sites of the bases. Then, in accord with base-pairing restrictions, each chain serves as a template for the synthesis of its complement. Accordingly, each daughter molecule contains one of the parental chains paired with a newly synthesized chain….

It also showed that the dispersive replication mechanism proposed by Delbruck, which had smaller subunits, was incorrect. The Meselson-Stahl experiment is a crucial experiment in biology. It decided between three proposed mechanisms for the replication of DNA. It supported the Watson-Crick semiconservative mechanism and eliminated the conservative and dispersive mechanisms. It played a similar role in biology to that of the experiments that demonstrated the nonconservation of parity did in physics.

Thus, we have seen evidence that experiment plays similar roles in both biology and physics and also that the same epistemological strategies are used in both disciplines. One interesting recent development in science, and thus in the philosophy of science, has been the increasing use of, and importance of, computer simulations. In some fields, such as high-energy physics, simulations are an essential part of all experiments. It is fair to say that without computer simulations these experiments would be impossible.

There has been a considerable literature in the philosophy of science discussing whether computer simulations are experiments, theory, or some new kind of hybrid method of doing science. Given the importance of computer simulations in science it is essential that we have good reasons to believe their results. Eric Winsberg , Wendy Parker and others have shown that scientists use strategies quite similar to those discussed in Section 1.

The distinction between observation and experiment is relatively little discussed in philosophical literature, despite its continuous relevance to the scientific community and beyond in understanding specific traits and segments of the scientific process and the knowledge it produces. Daston and her coauthors Daston ; Daston and Lunbeck ; Daston and Galison have convincingly demonstrated that the distinction has played a role in delineating various features of scientific practice.

It has helped scientists articulate their reflections on their own practice. Observation is philosophically a loaded term, yet the epistemic status of scientific observation has evolved gradually with the advance of scientific techniques of inquiry and the scientific communities pursuing them.

Daston succinctly summarizes this evolution in the following passage:. This aspect of the distinction has been a mainstay of understanding scientific practice ever since. Apart from this historical analysis, there are currently two prominent and opposed views of the experiment-observation distinction.

Ian Hacking has characterized it as well-defined, while avoiding the claim that observation and experiment are opposites Hacking , According to him, the notions signify different things in scientific practice.

The experiment is a thorough manipulation that creates a new phenomenon, and observation of the phenomenon is its outcome. If scientists can manipulate a domain of nature to such an extent that they can create a new phenomenon in a lab, a phenomenon that normally cannot be observed in nature, then they have truly observed the phenomenon Hacking , First, the uses of the distinction cannot be compared across scientific fields.

And second, as Gooding suggests, observation is a process too, not simply a static result of manipulation. Thus, both observation and experiment are seen as concurrent processes blended together in scientific practice. See also Chang A rather obvious danger of this approach is an over-emphasis on the continuousness of the notions of observation and experiment that results in inadvertent equivocation. And this, in turn, results in sidelining the distinction and its subtleties in the analysis of the scientific practice, despite their crucial role in articulating and developing that practice since the 17th century.

This issue certainly requires further philosophical and historical analysis. In this entry varying views on the nature of experimental results have been presented. Some argue that the acceptance of experimental results is based on epistemological arguments, whereas others base acceptance on future utility, social interests, or agreement with existing community commitments.

Everyone agrees , however, that for whatever reasons, a consensus is reached on experimental results. These results then play many important roles in physics and we have examined several of these roles, although certainly not all of them. We have seen experiment deciding between two competing theories, calling for a new theory, confirming a theory, refuting a theory, providing evidence that determined the mathematical form of a theory, and providing evidence for the existence of an elementary particle involved in an accepted theory.

We have also seen that experiment has a life of its own, independent of theory. If, as I believe, epistemological procedures provide grounds for reasonable belief in experimental results, then experiment can legitimately play the roles I have discussed and can provide the basis for scientific knowledge. We are grateful to Professor Carl Craver for both his comments on the manuscript and for his suggestions for further reading.

Experimental Results 1. The Roles of Experiment 2. Thomson and the Electron 2. For example, if we wish to argue that the spectrum of a substance obtained with a new type of spectrometer is correct, we might check that this new spectrometer could reproduce the known Balmer series in hydrogen. If we correctly observe the Balmer Series then we strengthen our belief that the spectrometer is working properly.

This also strengthens our belief in the results obtained with that spectrometer. If the check fails then we have good reason to question the results obtained with that apparatus.

Reproducing artifacts that are known in advance to be present. An example of this comes from experiments to measure the infrared spectra of organic molecules Randall et al. It was not always possible to prepare a pure sample of such material. Sometimes the experimenters had to place the substance in an oil paste or in solution.

In such cases, one expects to observe the spectrum of the oil or the solvent, superimposed on that of the substance. One can then compare the composite spectrum with the known spectrum of the oil or the solvent. Observation then of this artifact gives confidence in other measurements made with the spectrometer. Elimination of plausible sources of error and alternative explanations of the result the Sherlock Holmes strategy.

The only remaining explanation of their result was that it was due to electric discharges in the rings—there was no other plausible explanation of the observation. In addition, the same result was observed by both Voyager 1 and Voyager 2. This provided independent confirmation. Often, several epistemological strategies are used in the same experiment. Using the results themselves to argue for their validity. Although one might very well believe that his primitive, early telescope might have produced spurious spots of light, it is extremely implausible that the telescope would create images that they would appear to be a eclipses and other phenomena consistent with the motions of a small planetary system.

A similar argument was used by Robert Millikan to support his observation of the quantization of electric charge and his measurement of the charge of the electron. In both of these cases one is arguing that there was no plausible malfunction of the apparatus, or background, that would explain the observations. Using an independently well-corroborated theory of the phenomena to explain the results.

Although these experiments used very complex apparatuses and used other epistemological strategies for details see Franklin , pp. I believe that the agreement of the observations with the theoretical predictions of the particle properties helped to validate the experimental results. In this case the particle candidates were observed in events that contained an electron with high transverse momentum and in which there were no particle jets, just as predicted by the theory.

It was very improbable that any background effect, which might mimic the presence of the particle, would be in agreement with theory. Using an apparatus based on a well-corroborated theory. In this case the support for the theory inspires confidence in the apparatus based on that theory.

This is the case with the electron microscope and the radio telescope, whose operations are based on a well-supported theories, although other strategies are also used to validate the observations made with these instruments.

Using statistical arguments. An interesting example of this arose in the s when the search for new particles and resonances occupied a substantial fraction of the time and effort of those physicists working in experimental high-energy physics.

The usual technique was to plot the number of events observed as a function of the invariant mass of the final-state particles and to look for bumps above a smooth background.

The usual informal criterion for the presence of a new particle was that it resulted in a three standard-deviation effect above the background, a result that had a probability of 0.

This criterion was later changed to four standard deviations, which had a probability of 0. The advantages of a scientific instrument are that it cannot change theories. Instruments create an invariant relationship between their operations and the world, at least when we abstract from the expertise involved in their correct use. When our theories change, we may conceive of the significance of the instrument and the world with which it is interacting differently, and the datum of an instrument may change in significance, but the datum can nonetheless stay the same, and will typically be expected to do so.

An instrument reads 2 when exposed to some phenomenon. After a change in theory, [ 5 ] it will continue to show the same reading, even though we may take the reading to be no longer important, or to tell us something other than what we thought originally Ackermann , p. In discussing the discovery of weak neutral currents, Pickering states, Quite simply, particle physicists accepted the existence of the neutral current because they could see how to ply their trade more profitably in a world in which the neutral current was real.

He says: Achieving such relations of mutual support is, I suggest, the defining characteristic of the successful experiment. Pickering goes on to note that Morpurgo did not tinker with the two competing theories of the phenomena then on offer, those of integral and fractional charge: The initial source of doubt about the adequacy of the early stages of the experiment was precisely the fact that their findings—continuously distributed charges—were consonant with neither of the phenomenal models which Morpurgo was prepared to countenance.

Ackermann , p. Stable laboratory science arises when theories and laboratory equipment evolve in such a way that they match each other and are mutually self-vindicating. The dance of agency, seen asymmetrically from the human end, thus takes the form of a dialectic of resistance and accommodations, where resistance denotes the failure to achieve an intended capture of agency in practice, and accommodation an active human strategy of response to resistance, which can include revisions to goals and intentions as well as to the material form of the machine in question and to the human frame of gestures and social relations that surround it p.

The same could be done, I am sure, in respect of Fairbank. And these tracings are all that needs to said about their divergence. It just happened that the contingencies of resistance and accommodation worked out differently in the two instances. Differences like these are, I think, continually bubbling up in practice, without any special causes behind them pp. For an argument between myself and Franklin on the same lines as that laid out below, see Franklin , Chapter 8; Franklin ; and Pickering ; and for commentaries related to that debate, Ackermann and Lynch p.

The constructionist maintains a contingency thesis. In the case of physics, a physics theoretical, experimental, material could have developed in, for example, a nonquarky way, and, by the detailed standards that would have evolved with this alternative physics, could have been as successful as recent physics has been by its detailed standards. Moreover, b there is no sense in which this imagined physics would be equivalent to present physics. The physicist denies that.

Hacking , pp. For example: someone believes that the universe began with what for brevity we call a big bang. A host of reasons now supports this belief. It could equally have been advanced by an old-fashioned philosopher of language.

The constructionist holds that explanations for the stability of scientific belief involve, at least in part, elements that are external to the content of science. These elements typically include social factors, interests, networks, or however they be described. Opponents hold that whatever be the context of discovery, the explanation of stability is internal to the science itself Hacking , p.

Nevertheless, everyone seems to agree that a consensus does arise on experimental results. Appendix 6 2. Thomson and the Electron Experiment can also provide us with evidence for the existence of the entities involved in our theories. Epistemological strategies Examples from Kettlewell 1.

Experimental checks and calibration in which the apparatus reproduces known phenomena. Use of the scoring experiment to verify that the proposed scoring methods would be feasible and objective. Analysis of recapture figures for endemic betularia populations. Elimination of plausible sources of background and alternative explanations of the result.

Use of natural barriers to minimize migration. Filming the birds preying on the moths. Using an independently well-corroborated theory of the phenomenon to explain the results. Using an apparatus based on a well- corroborated theory. Use of Fisher, Ford, and Shepard techniques. Use and analysis of large numbers of moths.

Blind analysis Not used. Intervention, in which the experimenter manipulates the object under observation Not present Independent confirmation using different experiments. Use of two different types of traps to recapture the moths.

Key Takeaways: Experiments An experiment is a procedure designed to test a hypothesis as part of the scientific method.

The two key variables in any experiment are the independent and dependent variables. The independent variable is controlled or changed to test its effects on the dependent variable. Three key types of experiments are controlled experiments, field experiments, and natural experiments. Featured Video. Cite this Article Format. Helmenstine, Anne Marie, Ph. Definition and Design.

What Is an Experiment? Independent Variable Definition and Examples. Understanding Simple vs Controlled Experiments.

Dependent Variable Definition and Examples. Null Hypothesis Definition and Examples. Your Privacy Rights. To change or withdraw your consent choices for ThoughtCo. At any time, you can update your settings through the "EU Privacy" link at the bottom of any page. These choices will be signaled globally to our partners and will not affect browsing data.

We and our partners process data to: Actively scan device characteristics for identification. I Accept Show Purposes. You must record the results of the experiment. Researchers must interpret the results they receive, giving explanations for the data gathered. Most importantly, they must also draw a conclusion from the results. The conclusion must decide whether to accept or reject the hypothesis made at the beginning of the experiment.

It is often useful to display results with visual aids, such as graphs or charts, to help identify trends and relationships. Clayton Yuetter has worked as a professional writer since How to Calculate Experimental Value. What Are the 8 Steps in Scientific Research? How to Write a Summary on a Science Project. The Scientific Method for an Egg Drop.