In simple regression analysis, if the correlation coefficient is a positive value, then select one:

a. the slope of the regression line must also be positive.

b. the least squares regression equation could have either a positive or a negative slope.

c. the y-intercept must also be a positive value.

d. the coefficient of determination can be either positive or negative, depending on the value of the slope.

e. the standard error of estimate can have either a positive or a negative value.

When using simple regression, if the correlation coefficient is a positive value,  A. the slope of the regression line must also be positive.

The correlation coefficient shows the change in y as a result of a change in x. When this figure is positive, it means that the change in y is positive when there is a change in x.

This will then be represented graphically as a positive slope because the correlation coefficient is the mathematical representation of the slope.

In conclusion, the slope of a regression line will be positive when the correlation coefficient is positive.

Find out more at link.

(23*2)-12=x     x=34

step-by-step explanation:

step-by-step explanation:

what grade level is this? need to know so i can look in my old textbooks!