In simple linear regression, the slope represents the average change in the dependent variable (Y) for each one-unit increase in the independent variable (X). It captures both the direction (positive or negative) and the steepness of the relationship. For example, a slope of 2 means that for each unit increase in X, Y increases by 2 on average; a negative slope means Y decreases as X increases