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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?
Leave an answer
Our People Answers
1
(Based on todays review)
-
sonu36
Answer:
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.
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jillabean15
Answer:
the r2 value of the linearized model is greater than 0.977
Step-by-step explanation:
a p e x
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