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4. The following regression is fitted using variables identified that could be related to tuition charges ($) of a university. TUITION = α+ ẞ ACCEPT + y MSAT + 1 VSAT Where ACCEPT = the percentage of applicants that was accepted by the university, MSAT = Median Math SAT score for the freshman class and VSAT = Median English SAT score for the freshman class. The data was processed using MNITAB and the following is an extract of the output obtained: Predictor Coef StDev Τ Р Constant -26780 6115 -4.38 0.000 ACCEPT 116.00 37.17 * 0.003 MSAT -4.21 14.12 VSAT 70.85 15.77 -0.30 4.49 0.767 ** S = 2685 R-Sq = 69.6% R-Sq (adj) = 67.7% Analysis of Variance Source DF SS MS F Regression 3 808139371 Residual Error 49 Total 52 353193051 1161332421 269379790 7208021 37.37 Р 0.000 a) Write out the regression equation. b) State the dependent and independent variable(s) c) Fill in the blanks identified by ** and ****. d) Is ẞ significant, at the 10% level of significance? e) State one limitation of using the regression equation for predicting the value of the GPA score.

4. The following regression is fitted using variables identified that could be related to tuition charges ($) of a university. TUITION = α+ ẞ ACCEPT + y MSAT + 1 VSAT Where ACCEPT = the percentage of applicants that was accepted by the university, MSAT = Median Math SAT score for the freshman class and VSAT = Median English SAT score for the freshman class. The data was processed using MNITAB and the following is an extract of the output obtained: Predictor Coef StDev Τ Р Constant -26780 6115 -4.38 0.000 ACCEPT 116.00 37.17 * 0.003 MSAT -4.21 14.12 VSAT 70.85 15.77 -0.30 4.49 0.767 ** S = 2685 R-Sq = 69.6% R-Sq (adj) = 67.7% Analysis of Variance Source DF SS MS F Regression 3 808139371 Residual Error 49 Total 52 353193051 1161332421 269379790 7208021 37.37 Р 0.000 a) Write out the regression equation. b) State the dependent and independent variable(s) c) Fill in the blanks identified by ** and ****. d) Is ẞ significant, at the 10% level of significance? e) State one limitation of using the regression equation for predicting the value of the GPA score.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section: Chapter Questions
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4. The following regression is fitted using variables identified that could be related to tuition charges ($) of a university. TUITION = α+ ẞ ACCEPT + y MSAT + 1 VSAT Where ACCEPT = the percentage of applicants that was accepted by the university, MSAT = Median Math SAT score for the freshman class and VSAT = Median English SAT score for the freshman class. The data was processed using MNITAB and the following is an extract of the output obtained: Predictor Coef StDev Τ Р Constant -26780 6115 -4.38 0.000 ACCEPT 116.00 37.17 * 0.003 MSAT -4.21 14.12 VSAT 70.85 15.77 -0.30 4.49 0.767 ** S = 2685 R-Sq = 69.6% R-Sq (adj) = 67.7% Analysis of Variance Source DF SS MS F Regression 3 808139371 Residual Error 49 Total 52 353193051 1161332421 269379790 7208021 37.37 Р 0.000 a) Write out the regression equation. b) State the dependent and independent variable(s) c) Fill in the blanks identified by ** and ****. d) Is ẞ significant, at the 10% level of significance? e) State one limitation of using the regression equation for predicting the value of the GPA score.
Transcribed Image Text:4. The following regression is fitted using variables identified that could be related to tuition charges ($) of a university. TUITION = α+ ẞ ACCEPT + y MSAT + 1 VSAT Where ACCEPT = the percentage of applicants that was accepted by the university, MSAT = Median Math SAT score for the freshman class and VSAT = Median English SAT score for the freshman class. The data was processed using MNITAB and the following is an extract of the output obtained: Predictor Coef StDev Τ Р Constant -26780 6115 -4.38 0.000 ACCEPT 116.00 37.17 * 0.003 MSAT -4.21 14.12 VSAT 70.85 15.77 -0.30 4.49 0.767 ** S = 2685 R-Sq = 69.6% R-Sq (adj) = 67.7% Analysis of Variance Source DF SS MS F Regression 3 808139371 Residual Error 49 Total 52 353193051 1161332421 269379790 7208021 37.37 Р 0.000 a) Write out the regression equation. b) State the dependent and independent variable(s) c) Fill in the blanks identified by ** and ****. d) Is ẞ significant, at the 10% level of significance? e) State one limitation of using the regression equation for predicting the value of the GPA score.
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