Suppose that a least squares regression line equation is ˆy = 1.65 − 2.20x and the actual y value corresponding to x = 10 is −19, what is the residual value corresponding to y = −19?

Question
1. Suppose that a least squares regression line equation is ˆy = 1.65 − 2.20x and the actual y value corresponding to x = 10 is −19, what is the residual value corresponding to y = −19?
Step 1

Residual value:

The difference between the calculated value and predicted value of a dependent variable is defined as the residual value. Let e be the difference between the predicted value(y^) and the observed value (y), then the residual value is,

e = y – y^

Step 2

Computing the residual value:

Here, the least square regression equation is y^ = 1.65 – 2.20x.

The value of y^ at x=10 is obtained as shown below:

y^ = 1.65 – 2.20(10) = –20.35.

At x=10 the y-value is –...

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