Question

In the simple linear regression model estimate Y = b0 + b1X

Answer 1

Answer:

Option B) Y - estimated average predicted value, X – predictor, Y-intercept ($b_0$), slope ($b_1$)    

Step-by-step explanation:

In the simple linear regression model estimate is given by:

$Y = b_0 + b_1X$

Comparing this regression line with the slope intercept form, we get:

$y = mx + c$

where m is the slope of the straight line and c is the y-intercept that is the value of y when x is zero.

here,

Y is the predicted variable or the variable we need to predict

X is the predictor or the variable that helps us to predict Y

$b_1$ is the slope of the regression line.

$b_0$ is the y-intercept or the value of y when x is zero.

Thus, Option B)

Y - estimated average predicted value, X – predictor, Y-intercept ($b_0$), slope ($b_1$)