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?

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

Step-by-step 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.

my answer is$ 12

step-by-step explanation:

because 15 -2=12

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step-by-step explanation: