Question

The least squares regression equation for the data in the table is

= 13.5x + 42.9. The R-value is 0.977.

Why might you use a linearized model instead?

Answer 1

Explanation:

Answer 2

A linearized model would be the best in this case, since R \simeq 1 .

Explanation:

Since, R-value or the correlation coefficient is 0.977 or very close to 1, so

linearized model will be best suitable as least square regression model.

Since,

when R = 1

the points will accurately fall over a straight line having equation of the form

ax + by + c = 0 where a, b, c are fixed but otherwise arbitrary constants.