How is the slope of a regression line commonly expressed?

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The slope of a regression line represents the relationship between the independent variable (x) and the dependent variable (y). Specifically, it indicates how much the dependent variable is expected to change for a one-unit increase in the independent variable. This relationship is quantitatively expressed as "change in y over change in x," which illustrates the concept of rate of change.

When the slope is positive, it indicates that as x increases, y also increases, and when the slope is negative, it indicates that an increase in x results in a decrease in y. This fundamental aspect makes the slope a crucial component of understanding linear relationships in regression analysis.

The other options do not correctly reflect the concept of slope in regression. Standard deviation relates to the spread of data points and variability, the correlation coefficient measures the strength and direction of a linear relationship between two variables, and average mean pertains to the central tendency of a dataset.