[Solution] Use this multiple regression output to answer the given questions. SUMMARY OUTPUT Regression Statistics Multiple R 0.987606214 R Square 0.975366033

Question: Use this multiple regression output to answer the given questions.

SUMMARY OUTPUT

Regression Statistics
Multiple R	0.987606214
R Square	0.975366033
Adjusted R Square	0.975183108
Standard Error	5.34047778
Observations	408

ANOVA
	df	SS	MS	F	Significance F
Regression	3	456220.6	152073.5	5332.04	0
Residual	404	11522.36	28.5207
Total	407	467742.9

	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	302.1532811	13.04715	23.15856	4.05E-76	276.5045	327.8021
avgEngine_Speed (rpm)	-0.116140654	0.005488	-21.1619	1.97E-67	-0.12693	-0.10535
avgTorque (lb/ft)	-0.024792339	0.008247	-3.00621	0.2281	-0.041	-0.00858
avgPower (hp)	0.109661467	0.018464	5.93912	6.18E-09	0.073363	0.145959

What is the model (equation)?
Make an estimate with Rpm = 1200, Torque = 450 and Hp=210
Perform a global test for model adequacy.
Test each parameter for usefulness and indicate which ones are needed and which are NOT needed in the model.
How do you feel about this models predictive power?

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Solution: The downloadable solution consists of 2 pages
Deliverable: Word Document

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[Solution] Use this multiple regression output to answer the given questions. SUMMARY OUTPUT Regression Statistics Multiple R 0.987606214 R Square 0.975366033

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