why do we repeat experiments in science

Dont Repeat Yourself, DRY may be central tenet of computer programming doctrine, but is it not part of the chemists credo. Scientists spend a significant amount of time repeating procedures and even experiments in the quest to push back the frontiers of human knowledge. If we want to create and discover new knowledge, why do we spend so much time repeating what has been done before? There are several good reasons why experiments need to be repeated:
The first reason to repeat experiments is simply to verify results. Different science disciplines have different criteria for determining what good results are.


Biological assays, for example must be done in at least triplicate to generate acceptable data. Science is built on the assumption that published experimental protocols are repeatable. The next reason to repeat experiments is to develop skills necessary to extend established methods and develop new experiments. Practice make perfect is true for the concert hall and the chemical laboratory. Refining experimental observations is another reason to repeat. Maybe you did not follow the progress of the reaction like you should have.


Another reason to repeat experiments is to study and/or improve them in way. In the synthetic chemistry laboratory, for example, there is always a desire to improve the yield of a synthetic step. Will certain changes in the experimental conditions lead to a better yield? The only way to find out is to try it! The scientific method informs us that it is best to only make one change at a time. The final reason to repeat an extraction, chromatographic or synthetic protocol is to produce more of your target substance.


This is sometimes referred to scale-up. Many people may have ideas about why materials have different properties, but these opinions are not very useful if they are not supported by data. To justify an explanation, you need to have data to support it. This data may be obtained by taking measurements. The accuracy of each measurement depends on the quality of the measuring apparatus and the skill of the scientists taking the measurement. If the apparatus is faulty, or the scientists make a mistake, the measurement may be inaccurate.


For the data to be reliable, the variation within the values must be small. There is always some variation in any set of measurements, whatever is being measured. There may be small differences in the composition of the rubber or the way the measuring apparatus is used. In this set of data, each measurement is only slightly different from the others. The results are repeatable, meaning that each time a measurement is taken it has approximately the same value. We can say that this set of data is reliable.

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