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Unformatted text preview: uares regression equation, predicted value of Y when X = 3.25? A. 15.42 B. 15.61 C. 27.78 D. 44.92 = 12.36 + 4.745(X), and determine the = 12.36 + 4.745(3.25) = 27.78 AACSB: Analytic Bloom's: Application Difficulty: Easy Learning Objective: 1 Topic: Simple Linear Regression 127. Consider the following partial computer output from a simple linear regression analysis. What is the estimated y-intercept? A. 1.12 B. -28.13 C. 22.90 D. .99 AACSB: Analytic Bloom's: Application Difficulty: Easy Learning Objective: 4 Topic: Simple Linear Regression 1-1280 Chapter 01 - An Introduction to Business Statistics 128. Consider the following partial computer output from a simple linear regression analysis. What is the estimated slope? A. 1.12 B. -28.13 C. 22.90 D. .05 AACSB: Analytic Bloom's: Application Difficulty: Easy Learning Objective: 4 Topic: Simple Linear Regression 129. Consider the following partial computer output from a simple linear regression analysis. Write the equation of the least squares line. A. ŷ = 1.12 - 28.13x B. ŷ = -28.13 + 1.12 C. ŷ = -28.13 + 1.12x D. ŷ = 1.12 + .04891x AACSB: Analytic Bloom's: Application Difficulty: Easy Learning Objective: 4 Topic: Simple Linear Regression 1-1281 Chapter 01 - An Introduction to Business Statistics 130. Consider the following partial computer output from a simple linear regression analysis. Test H0: β1 ≤ 0 vs. Ha: β1 > 0. A. .088, fail to reject null hypothesis B. 22.895, reject the null hypothesis C. .088, reject the null hypothesis D. 22.895, fail to reject the null hypothesis .0001 < .05, reject H0 AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 4 Topic: Significance of the slope 131. Consider the following partial computer output from a simple linear regression analysis. What is the predicted value of y when x = 1,000? A. 1148.13 B. -27.01 C. 1091.87 D. 1142.90 = -28.13 + 1.12(1000) = 1091.87 AACSB: Analytic Bloom's: Application Difficulty: Easy Learning Objective: 4 Topic: Simple Linear Regression 1-1282 Chapter 01 - An Introduction to Business Statistics 132. Consider the following partial computer output from a simple linear regression analysis. Calculate the correlation coefficient. A. .9722 B. .986 C. -.088 D. .2968 AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 6 Topic: Correlation 1-1283 Chapter 01 - An Introduction to Business Statistics 133. Complete the following partial ANOVA table from a simple linear regression analysis with a sample size of 16 observations. Find the F test to test the significance of the model. A. 3.214 B. 6.78 C. 6.33 D. 4.60 F = 6.33, reject H0 F.05,1,14 = 4.60 6.33 > 4.60, reject H0. AACSB: Analytic Bloom's: Application Difficulty: Hard Learning Objective: 8 Topic: F test 1-1284 Chapter 01 - An Introduction to Business Statistics 134. Consider the following partial computer output from a simple linear regression analysis with a sample size of 16 observations. Find the t test to test the significance of the model. A. 2.52 B. 2.61 C. 2.15 D. 2.65 t = 2.52, reject H0 AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 4 Topic: Significance of the slope 1-1285 Chapter 01 - An Introduction to Business Statistics 135. Consider the following partial computer output from a simple linear regression analysis. S = 0.4862 R-Sq = ______ Analysis of Variance What is the estimated y-intercept? A. 4.862 B. -0.347 C. .5201 D. .8089 AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 4 Topic: Simple Linear Regression 1-1286 Chapter 01 - An Introduction to Business Statistics 136. Consider the following partial computer output from a simple linear regression analysis. S = 0.4862 R-Sq = ______ Analysis of Variance What is the estimated slope? A. 4.862 B. -0.347 C. .5201 D. .05866 AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 4 Topic: Simple Linear Regression 1-1287 Chapter 01 - An Introduction to Business Statistics 137. Consider the following partial computer output from a simple linear regression analysis. S = 0.4862 R-Sq = ______ Analysis of Variance Write the equation of the least squares line. A. y = 4.8615 + 0.34655x B. y = -.34655 + 4.8615x C. y = 4.8615 - .34655x D. y = .5201 + .05866x y = 4.8615 -0.34655 x AACSB: Analytic Bloom's: Application Difficulty: Easy Learning Objective: 1 Topic: Simple Linear Regression 1-1288 Chapter 01 - An Introduction to Business Statistics 138. Consider the following partial computer output from a simple linear regression analysis. S = 0.4862 R-Sq = ______ Analysis of Variance Test H0: = .001. What do you conclude about the 1 = 0 versus Ha: 1 ≠ 0 by setting relationship between y and x? A. Reject the null hypothesis, significant linear relationship between x and y B. Fail to reject the null hypothesis, no evidence of a linear relationship between x and y -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 i...
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This document was uploaded on 01/20/2014.

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