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Question: The complete modelE(y)=β0+β1x1+β2x2+β3x3+β4x4+εwas fit to n = 20 data points, with SSE = 152.66. The reduced model,E(y)=β0+β1x1+β2x2+ε, was also fit, with

SSE = 160.44.

a. How many β parameters are in the complete model? The reduced model?

b. Specify the null and alternative hypotheses you would use to investigate whether the complete model contributes more information for the prediction of y than the reduced model.

c. Conduct the hypothesis test of part b. Use α = .05.

Short Answer

Expert verified

Answer

a. The no. of β parameters in complete model are 5 and the no of β parameters in reduced model are 3.

b. The null and alternate hypothesis to test whether the complete model contributes more information for the prediction of y than the reduced model can be written as H0: β3 = β4 = β5 = 0 while Ha: At least one of β parameters are nonzero

c. At 95% confidence interval there is enough evidence to not reject H0

Step by step solution

01

No of β parameters

The no. of β parameters in complete model are 4 and the no of β parameters in reduced model are 3.

02

 Step 2: Hypotheses

The null and alternate hypothesis to test whether the complete model contributes more information for the prediction of y than the reduced model can be written as

H0: β3 = β4 = 0 while Ha: At least one of β parameters are nonzero.

03

Thesis testing

H0: β3 = β4 = 0 and Ha: At least one of β parameters are nonzero

Teststatistic=((SSER-SSEC)/(k-g))(SSEC/[n-(k-1)])=0.38222

For α = .05, F-test statistic = 3.009. H0 is rejected if F-statistic > F

Here, 0.38222 < 3.009.

Therefore, at 95% confidence interval there is enough evidence to not reject H0.

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Most popular questions from this chapter

Going for it on fourth down in the NFL. Refer to the Chance (Winter 2009) study of fourth-down decisions by coaches in the National Football League (NFL), Exercise 11.69 (p. 679). Recall that statisticians at California State University, Northridge, fit a straight-line model for predicting the number of points scored (y) by a team that has a first-down with a given number of yards (x) from the opposing goal line. A second model fit to data collected on five NFL teams from a recent season was the quadratic regression model, E(y)=β0+β1x+β2x2.The regression yielded the following results: y=6.13+0.141x-0.0009x2,R2=0.226.

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