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spr10_ex3

spr10_ex3 - STA 6127 Exam 3 Spring 2010 PRINT Name Q.1 A...

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STA 6127 – Exam 3 – Spring 2010 PRINT Name __________________________ Q.1. A linear regression model is fit, relating Y=Math Score on a standardized exam to Age and Education level. The following output gives the results of the regression model. Complete the parts below the output. The model is: E(Y) = α + β A AGE + β E EDU ANOVA df SS MS F P-value Regression 2 569545 284772.5 43.65623 0.0000 Residual 27 176122.8 6523.067 Total 29 745667.8 Coefficients tandard Err t Stat P-value Lower 95%Upper 95% Intercept -100.69 341.66 -0.2947 0.7705 -801.72 600.33 Age 44.72 51.93 0.8612 0.3967 -61.83 151.27 Education 61.55 49.24 1.2499 0.2221 -39.49 162.58 p.1.a. Give the predicted score for a child whose AGE=12.0 and EDU = 6. ________________________ p.1.b. Give the test statistic and P-value for testing H 0 : β A = β E =0 Test Stat ________ P- Value ______ p.1.c. Give the test statistic and P-value for testing H 0 : β A =0 Test Stat ________ P-Value ______ p.1.d. Give the test statistic and P-value for testing H 0 : β E =0 Test Stat ________ P-Value ______ p.1.e. Which statement best describes the results of the experiment (Choose only one) i) Neither Age or Education are associated with math scores ii) Adjusting for Age, Education is associated with math scores iii) Adjusting for Education, Age is associated with math scores iv) As a “group” of variables, Education and Age are associated with math scores p.1.f. This appears to be an example where multicollinearity exists

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spr10_ex3 - STA 6127 Exam 3 Spring 2010 PRINT Name Q.1 A...

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