An experimental study involves taking manipulating the system, measurements of the system under study, and if the manipulation has modified the values of the measurements then taking additional measurements using the same procedure to determine. Experimental studies are also known as repeated-measures. Because you do more than just observe the subjects they are also referred to as interventions.

The Importance of additional data from experimental studies:

Rather than the full population, you always have to work with a sample of subjects. The sample has to be representative of the population, to generalize from the sample to the population. To use a random selection procedure the safest way to ensure that it is representative. Make sure that you have representation of population subgroups (e.g. races, regions sexes,). Additional data from experimental studies helps you to use a stratified random sampling procedure; selection bias is a possible when the sample is not representative of the population. To control and treatment groups in experiments can also produce bias Failure to randomize subjects. Into the groups if you let people select themselves, or make one group different from another if you select the groups in any way that, rather than an effect of the treatment then any result you get might reflect the group difference. For this reason, it’s important to have additional data in terms of important variables that could modify the effect of the treatment (e.g., gender, age, and performance, physical) to assign subjects in a way that ensures the groups are balanced.

Author: Murat Artiran, Ph. D., Clinical Psychologist