The correlation is the covariance divided by the product of the standard deviations. In a regression context the slope is the heart and soul of the equation because it tells you how much you can expect Y to change as X increases. Regression formula is used to assess the relationship between dependent and independent variable and find out how it affects the dependent variable on the change of independent variable and represented by equation Y is equal to aX plus b where Y is the dependent variable a is the slope of regression equation x is the independent variable and b is constant.
In non-parametric statistics the TheilSen estimator is a method for robustly fitting a line to sample points in the plane simple linear regression by choosing the median of the slopes of all lines through pairs of points.
The table gives the number of songs downloaded from MyTunes at different prices per song. 066 in the equation is the slope of the linear regression which defines how much of the variable is the dependent variable on the independent variable. The coefficient and slope is positive 5. And the predicted response haty_i is an unbiased estimate of mu_Y if the mean of all of the possible predicted responses haty_i equals mu_Y.