Randomization is a crucial component of experimental design, and it’s important for several reasons:
Prevents bias: Randomization ensures that each participant has an equal chance of being assigned to any condition, minimizing the potential for bias in the assignment process.
Controls for confounding variables: Randomization helps to distribute confounding variables evenly across conditions, reducing the risk of spurious correlations between the independent variable and the outcome.
Increases internal validity: By randomly assigning participants to conditions, you can increase the confidence that any observed differences between conditions are due to the independent variable and not some other factor.