

Linear regression fits this model to your data:
The slope quantifies the steepness of the line. It equals the change in Y for each unit change in X. It is expressed in the units of the Y axis divided by the units of the X axis. If the slope is positive, Y increases as X increases. If the slope is negative, Y decreases as X increases.
The Y intercept is the Y value of the line when X equals zero. It defines the elevation of the line.
Correlation and linear regression are not the same. Review the differences.
Simple linear regression is shown above. There is only a single X variable. In contrast, multiple linear regression defines Y as a function that includes several X variables.