91Ó°ÊÓ

The mean squared discrepancies among both experimental and theoretical values is lessened by the regression line.

The linear regression relates the mean scores of the X and Y components.

The $y-$intercept of the population regression line

${\mathrm{β}}_0$Is the $y-$intercept of the population regression line$y={\mathrm{β}}_0+6{\mathrm{β}}_1.$

The mean squared discrepancies among both experimental and theoretical values is lessened by the regression line.

The linear regression relates the mean scores of the X and Y components.

${\mathrm{β}}_1$ is the slope of regression line$y={\mathrm{β}}_0+x{\mathrm{β}}_1$.

The mean squared discrepancies among both experimental and theoretical values is lessened by the regression line.

The linear regression relates the mean scores of the X and Y components.

The standard error of the estimate is the statistic used to produce a point estimate for the common conditional standard deviation $\mathrm{σ}$.

$S_e=\sqrt{\frac{SSE}{n-2}}$.