This process is an important research tool used in psychology research, allowing scientists to create representative samples from which conclusions can be drawn and applied to the larger population.
One thing that is important to note is that random selection is not the same thing as random assignment.
In this case, we’re talking about random Random assignment might involve flipping a coin, drawing names out of a hat, or using random numbers.
All subjects should have the same probability of being assigned to any group.
Because activity increases bone density, the higher activity in the treatment group may account for the greater bone density compared to the less active control group.
Because it is not in the model, activity is a confounding variable that makes the jumping exercise appear to be significant when it might not be.For example, random selection might be used to draw 100 students to participate in a study.Each of these 100 participants would then be randomly assigned to either the control group or the experimental group.While random selection involves how participants are chosen for a study, random assignment involves how those chosen are then assigned to different groups in the experiment.Many studies and experiments actually use both of these techniques.Further, let’s assume that greater physical activity is correlated with increased bone density but we didn’t measure it. Scenario 1: We don’t use random assignment and, unbeknownst to us, the more physically active subjects end up in the treatment group.The treatment group starts out more active than the control group.For both scenarios, the data and statistical results could be identical.However, the results for the second scenario are more valid thanks to the methodology.Leaving a confounding variable out of a statistical model can make an included predictor look falsely insignificant or falsely significant.In other words, they can totally flip your statistical analysis results on its head!