Error variance must be minimized in an experiment because it
A)leads to confounding.
B)makes the effects of the independent variable harder to detect.
C)leads to differential attrition.
D)increases expectancy effects.

Question

Quizplus · Accepted Answer

Error variance refers to the variability in scores that is not due to the independent variable but rather to other, uncontrolled variables. Minimizing error variance is crucial because it makes the effects of the independent variable clearer and easier to detect. High error variance can mask the true impact of the independent variable, making it difficult to determine whether any observed effects are actually due to the manipulation of the independent variable or to some other, uncontrolled factors.

Error Variance Must Be Minimized in an Experiment Because It