The following table shows the sets of data $\left(x,y\right)$(x,y) and the predicted $\hat{y}$^y values based on a least-squares regression line. Complete the table by finding the residuals.
$x$x-values | $1$1 | $3$3 | $5$5 | $7$7 | $9$9 |
---|---|---|---|---|---|
$y$y-values | $22.7$22.7 | $22.3$22.3 | $24.2$24.2 | $21.8$21.8 | $21.5$21.5 |
$\hat{y}$^y | $25.2$25.2 | $23.4$23.4 | $21.6$21.6 | $19.8$19.8 | $18$18 |
Residuals | $\editable{}$ | $\editable{}$ | $\editable{}$ | $\editable{}$ | $\editable{}$ |
The following table shows the sets of data $\left(x,y\right)$(x,y) and the predicted $\hat{y}$^y-values based on a least-squares regression line. Complete the table by finding the residuals.
If a residual is a positive value, is the actual value of the response variable above or below the least squares regression line?
If a measured point in a data set is below the least squares regression line, will the corresponding residual be positive or negative?