Linear regression describes the extent to which predicts . X; Y the predictor variable; the criterion variable the known variable; the to-be-predicted variable all of the above

 the known variable; the to-be-predicted variable

Step-by-step explanation:

In statistics, linear regression is a technique to model the relationship between two variables ( one independent and other dependent).

It requires some previous data to plot a best fit line.

It is used to predict the values for dependent variable for each independent variable.

Here, independent variable = known variable and dependent variable = is to be predicted

Hence, Linear regression describes the extent to which the known variable predicts the to-be-predicted variable.

c > -10.55

step-by-step explanation: