Which coefficient indicates how much the dependent variable changes for a one-unit change in an independent variable in regression analysis?

In regression analysis, the slope coefficient provides insight into the relationship between the independent variable and the dependent variable. Specifically, it quantifies the amount of change in the dependent variable that is associated with a one-unit change in the independent variable. This coefficient illustrates the strength and direction of the linear relationship—whether it is positive or negative.

For instance, if the slope coefficient is 2, this means that for every one-unit increase in the independent variable, the dependent variable is expected to increase by 2 units. This characteristic of slope coefficients makes them essential for interpreting regression results and for making predictions based on the model.

Other coefficients mentioned do not fulfill this function: the coefficient of determination assesses the proportion of variance in the dependent variable explained by the independent variable(s), the intercept coefficient represents the expected value of the dependent variable when all independent variables are zero, and the correlation coefficient measures the strength and direction of a linear relationship between two variables rather than indicating specific changes in the dependent variable due to changes in the independent variable.