Final answer:
The slope of a simple regression line represents the change in the dependent variable (y) for every unit change in the independent variable (x). It can be calculated by dividing the difference in the y-values by the difference in the x-values between two points on the line.
Step-by-step explanation:
The slope of a simple regression line represents the change in the dependent variable (y) for every unit change in the independent variable (x). It can be calculated by dividing the difference in the y-values (the rise) by the difference in the x-values (the run) between two points on the line.
For example, if the slope is 3, it means that for every increase of 1 in the x-value, the y-value increases by 3. This relationship holds true for any point along the straight line.
The slope is denoted by the variable m in the equation y = mx + b, where b represents the y-intercept, the point at which the line crosses the vertical axis.