what treatment is being compared to the control in the experiment

Methods employed to reduce mistake in science tests

Take identical growing plants (Argyroxiphium sandwicense) and give fertilizer to half of them. If there are differences between the fertilized treatment and the unfertilized treatment, these differences may exist due to the fertilizer equally long as at that place weren't other misreckoning factors that affected the result. For example, if the fertilizer was spread by a tractor just no tractor was used on the unfertilized treatment, and so the effect of the tractor needs to be controlled.

A scientific control is an experiment or observation designed to minimize the effects of variables other than the contained variable (i.due east. misreckoning variables).^[1] This increases the reliability of the results, oftentimes through a comparison between command measurements and the other measurements. Scientific controls are a part of the scientific method.

Controlled experiments [edit]

Controls eliminate alternate explanations of experimental results, especially experimental errors and experimenter bias. Many controls are specific to the type of experiment being performed, equally in the molecular markers used in SDS-PAGE experiments, and may merely have the purpose of ensuring that the equipment is working properly. The pick and use of proper controls to ensure that experimental results are valid (for instance, absence of confounding variables) can be very difficult. Control measurements may also be used for other purposes: for example, a measurement of a microphone'south background racket in the absence of a signal allows the noise to be subtracted from afterwards measurements of the bespeak, thus producing a processed signal of higher quality.

For example, if a researcher feeds an experimental artificial sweetener to threescore laboratories rats and observes that 10 of them later become sick, the underlying cause could exist the sweetener itself or something unrelated. Other variables, which may not be readily obvious, may interfere with the experimental blueprint. For instance, the artificial sweetener might be mixed with a dilutant and it might be the dilutant that causes the effect. To control for the effect of the dilutant, the same test is run twice; once with the artificial sweetener in the dilutant, and another done exactly the same way but using the dilutant alone. At present the experiment is controlled for the dilutant and the experimenter can distinguish between sweetener, dilutant, and non-handling. Controls are nearly oft necessary where a confounding factor cannot easily be separated from the primary treatments. For instance, it may be necessary to use a tractor to spread fertilizer where at that place is no other practicable way to spread fertilizer. The simplest solution is to have a treatment where a tractor is driven over plots without spreading fertilizer and in that way, the effects of tractor traffic are controlled.

The simplest types of control are negative and positive controls, and both are constitute in many different types of experiments.^[2] These two controls, when both are successful, are usually sufficient to eliminate most potential confounding variables: information technology means that the experiment produces a negative result when a negative result is expected, and a positive upshot when a positive consequence is expected.

Negative [edit]

Where in that location are only ii possible outcomes, east.g. positive or negative, if the treatment group and the negative control both produce a negative result, it tin can exist inferred that the treatment had no effect. If the treatment group and the negative control both produce a positive outcome, it can exist inferred that a confounding variable is involved in the phenomenon nether study, and the positive results are not solely due to the handling.

In other examples, outcomes might be measured equally lengths, times, percentages, and so forth. In the drug testing case, we could measure the pct of patients cured. In this instance, the treatment is inferred to take no effect when the treatment group and the negative command produce the aforementioned results. Some improvement is expected in the placebo grouping due to the placebo outcome, and this result sets the baseline upon which the treatment must amend upon. Even if the treatment group shows improvement, information technology needs to be compared to the placebo group. If the groups show the aforementioned upshot, then the treatment was not responsible for the improvement (considering the same number of patients were cured in the absenteeism of the handling). The treatment is merely constructive if the handling group shows more comeback than the placebo group.

Positive [edit]

Positive controls are often used to assess exam validity. For example, to assess a new test's ability to detect a affliction (its sensitivity), and so we tin can compare it against a different test that is already known to work. The well-established examination is a positive control since we already know that the answer to the question (whether the exam works) is yes.

Similarly, in an enzyme assay to measure the amount of an enzyme in a prepare of extracts, a positive control would be an assay containing a known quantity of the purified enzyme (while a negative control would comprise no enzyme). The positive control should give a large amount of enzyme activeness, while the negative command should give very depression to no activity.

If the positive command does not produce the expected issue, there may be something wrong with the experimental procedure, and the experiment is repeated. For hard or complicated experiments, the upshot from the positive control tin as well help in comparison to previous experimental results. For example, if the well-established disease exam was adamant to have the same effect every bit found by previous experimenters, this indicates that the experiment is existence performed in the same way that the previous experimenters did.

When possible, multiple positive controls may be used—if there is more than one disease examination that is known to be constructive, more one might be tested. Multiple positive controls also allow effectively comparisons of the results (calibration, or standardization) if the expected results from the positive controls have different sizes. For example, in the enzyme assay discussed above, a standard curve may exist produced past making many different samples with dissimilar quantities of the enzyme.

Randomization [edit]

In randomization, the groups that receive different experimental treatments are adamant randomly. While this does not ensure that in that location are no differences betwixt the groups, it ensures that the differences are distributed equally, thus correcting for systematic errors.

For instance, in experiments where crop yield is afflicted (east.grand. soil fertility), the experiment can exist controlled by assigning the treatments to randomly selected plots of land. This mitigates the result of variations in soil composition on the yield.

Blind experiments [edit]

Blinding is the practice of withholding information that may bias an experiment. For case, participants may not know who received an active treatment and who received a placebo. If this information were to become available to trial participants, patients could receive a larger placebo outcome, researchers could influence the experiment to meet their expectations (the observer consequence), and evaluators could be subject to confirmation bias. A bullheaded can be imposed on whatever participant of an experiment, including subjects, researchers, technicians, data analysts, and evaluators. In some cases, sham surgery may exist necessary to achieve blinding.

During the course of an experiment, a participant becomes unblinded if they deduce or otherwise obtain data that has been masked to them. Unblinding that occurs before the conclusion of a study is a source of experimental mistake, every bit the bias that was eliminated by blinding is re-introduced. Unblinding is mutual in bullheaded experiments and must exist measured and reported. Meta-research has revealed high levels of unblinding in pharmacological trials. In particular, antidepressant trials are poorly blinded. Reporting guidelines recommend that all studies assess and report unblinding. In exercise, very few studies assess unblinding.^[3]

Blinding is an important tool of the scientific method, and is used in many fields of research. In some fields, such as medicine, it is considered essential.^[4] In clinical research, a trial that is not blinded trial is called an open trial.

See also [edit]

• False positives and false negatives
• Designed experiment
• Controlling for a variable
• James Lind cured scurvy using a controlled experiment that has been described as the first clinical trial.^{[five] [6]}
• Wait list command grouping

References [edit]

1. ^ Life, Vol. II: Development, Diversity and Ecology: (Chs. 1, 21–33, 52–57). W. H. Freeman. 2006. p. 15. ISBN978-0-7167-7674-1 . Retrieved 14 February 2015.
2. ^ Johnson PD, Besselsen DG (2002). "Practical aspects of experimental blueprint in animal inquiry" (PDF). ILAR J. 43 (four): 202–206. doi:10.1093/ilar.43.4.202. PMID 12391395. Archived from the original (PDF) on 2010-05-29.
3. ^ Bello, Segun; Moustgaard, Helene; Hróbjartsson, Asbjørn (Oct 2014). "The adventure of unblinding was infrequently and incompletely reported in 300 randomized clinical trial publications". Periodical of Clinical Epidemiology. 67 (10): 1059–1069. doi:x.1016/j.jclinepi.2014.05.007. ISSN 1878-5921. PMID 24973822.
4. ^ "Oxford Centre for Evidence-based Medicine – Levels of Evidence (March 2009)". cebm.net. 11 June 2009. Archived from the original on 26 October 2017. Retrieved two May 2018.
5. ^ James Lind (1753). A Treatise of the Scurvy. PDF
6. ^ Simon, Harvey B. (2002). The Harvard Medical School guide to men'south health . New York: Gratis Printing. p. 31. ISBN0-684-87181-v.

External links [edit]

• "Control". Encyclopædia Britannica. Vol. 7 (11th ed.). 1911.

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Source: https://en.wikipedia.org/wiki/Scientific_control

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