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# 088 reject the null hypothesis d 22895 fail to reject

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Unformatted text preview: s a significant linear relationship between x and y. AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 4 Topic: Significance of the slope 1-1289 Chapter 01 - An Introduction to Business Statistics 139. Consider the following partial computer output from a simple linear regression analysis. S = 0.4862 R-Sq = ______ Analysis of Variance Calculate the t statistic used to test H0: A. -5.908 B. -4.221 C. 5.908 D. 4.221 1 = 0 versus Ha: 1 ≠ 0 at α = .001. -0.34655/0.05866 = -5.908 compared to t statistic of -4.221 (for = .001, df = 13) so reject the null hypothesis at .001. There is a significant linear relationship between x and y. AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 4 Topic: Significance of the slope 1-1290 Chapter 01 - An Introduction to Business Statistics 140. Consider the following partial computer output from a simple linear regression analysis. S = 0.4862 R-Sq = ______ Analysis of Variance What is the predicted value of y when x = 9.00? A. 7.980 B. -1.743 C. -4.1385 D. 1.743 y = 4.8615 - 0.34655 (9.00) = 1.743 AACSB: Analytic Bloom's: Application Difficulty: Easy Learning Objective: 1 Topic: Simple Linear Regression 1-1291 Chapter 01 - An Introduction to Business Statistics 141. Consider the following partial computer output from a simple linear regression analysis. S = 0.4862 R-Sq = ______ Analysis of Variance Calculate the MSE. A. .4862 B. .6973 C. .2364 D. .5201 MSE = s2 = (.4862)2 = 0.2364 AACSB: Analytic Bloom's: Application Difficulty: Hard Learning Objective: 3 Topic: Simple Linear Regression 1-1292 Chapter 01 - An Introduction to Business Statistics 142. Consider the following partial computer output from a simple linear regression analysis. S = 0.4862 R-Sq = ______ Analysis of Variance Calculate the SSE A. 3.073 B. 6.321 C. 3.310 D. 11.324 SSE = MSE * (n-2) = .2364 * (13) = 3.073 AACSB: Analytic Bloom's: Application Difficulty: Hard Learning Objective: 3 Topic: Simple Linear Regression 1-1293 Chapter 01 - An Introduction to Business Statistics 143. Consider the following partial computer output from a simple linear regression analysis. S = 0.4862 R-Sq = ______ Analysis of Variance What is the unexplained variance? A. 11.324 B. 3.073 C. 6.321 D. 3.310 Unexplained variance = SSE = 3.073 AACSB: Analytic Bloom's: Application Difficulty: Hard Learning Objective: 6 Topic: Simple Linear Regression 1-1294 Chapter 01 - An Introduction to Business Statistics 144. Consider the following partial computer output from a simple linear regression analysis. S = 0.4862 R-Sq = ______ Analysis of Variance What is the explained variance? A. 11.324 B. 3.073 C. 8.251 D. 6.321 Explained variance = Total variance - Unexplained variance = 11.324 - 3.073 = 8.251 AACSB: Analytic Bloom's: Application Difficulty: Easy Learning Objective: 6 Topic: Simple Linear Regression 1-1295 Chapter 01 - An Introduction to Business Statistics 145. Consider the following partial computer output from a simple linear regression analysis. S = 0.4862 R-Sq = ______ Analysis of Variance What is the coefficient of determination? A. .8536 B. .7286 C. .2714 D. .3724 r2 = Explained variance/Total variance = 8.251/11.324 = .7286 Explained variance = Total variance - Unexplained variance = 11.324 - 3.073 = 8.251 AACSB: Analytic Bloom's: Application Difficulty: Hard Learning Objective: 6 Topic: Coefficient of determination 1-1296 Chapter 01 - An Introduction to Business Statistics 146. Consider the following partial computer output from a simple linear regression analysis. S = 0.4862 R-Sq = 0.7286 Analysis of Variance What is the correlation coefficient? A. .8536 B. .7286 C. .4862 D. -.8536 r = √.7286 = -0.8536 (use the sign of the slope) AACSB: Analytic Bloom's: Application Difficulty: Hard Learning Objective: 6 Topic: Correlation 1-1297 Chapter 01 - An Introduction to Business Statistics 147. Consider the following partial computer output from a simple linear regression analysis. S = 0.4862 R-Sq = ______ Analysis of Variance Determine the 95% confidence interval for the mean value of y when x = 9.00. Givens: ∑ x = 129.03 and ∑ x2 = 1178.547 A. (.6572 2.829) B. (1.467 2.019) C. (.6718 .2814) D. (1.471 2.015) Y = 1.743 Distance value = 1/15 + [(9-(129.03/15))2/(1178.547 - (129.03)2/15))] = .068975 t statistic = 2.160 y ± (t) (s) (√dv) 1.743 ± (2.160) (.4862) (√.068975) → 1.467 to 2.019 AACSB: Analytic Bloom's: Application Difficulty: Hard Learning Objective: 5 Topic: Confidence & prediction intervals 1-1298 Chapter 01 - An Introduction to Business Statistics 148. Consider the following partial computer output from a simple linear regression analysis. S = 0.4862 R-Sq = ______ Analysis of Variance Determine the 95% prediction interval for the mean value of y when x = 9.00 Givens: ∑ x = 129.03 and ∑ x2 = 1178.547 A. (.6572 2.829) B. (1.467 2.019) C. (.6718 .2814) D. (1.471 2.015) Y = 1.743 Distance value = 1/15 + [(9 - (129.03/15))2/(1178.547 - (129.03)2/15))] = .068975 t statistic = 2....
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