What term describes the magnitude of change that an independent variable has on a dependent variable?

The term "Effect Size" quantifies the magnitude of change that an independent variable exerts on a dependent variable, providing a standardized measure of the strength of the relationship or the impact of the independent variable. It allows researchers to understand not just whether a significant difference exists, but how substantial that difference is. This concept is crucial in research as it helps in interpreting the practical significance of the findings, beyond mere statistical significance.

In contrast, statistical power refers to the probability of correctly rejecting a null hypothesis when it is false, which relates to the likelihood of detecting an effect but does not quantify its size. Variance measures the extent to which data points differ from the mean, serving more as a descriptive statistic than an indicator of the effect of one variable on another. A confidence interval provides a range of values that is likely to contain the true parameter value, reflecting the measure of uncertainty rather than the strength of the effect. Thus, "Effect Size" is the most appropriate term for assessing how significant an independent variable's influence is on a dependent variable.