1-20chapter stats

A 1951 4049 b 4552 6552 c 0492 20492 d 0259

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: ting of monthly tire sales (in thousands of tires) and monthly advertising expenditures (in thousands of dollars). The simple linear regression equation is = 3 + 1X. The dealer randomly selects one of the six observations with a monthly sales value of 8000 tires and monthly advertising expenditures of $7000. Calculate the value of the residual for this observation. A. 1 B. -2 C. 2 D. -1 = 3 + 1(7) = 10 e = 8 - 10 = -2 AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 9 Topic: Residual analysis 1-1270 Chapter 01 - An Introduction to Business Statistics 117. A local tire dealer wants to predict the number of tires sold each month. He believes that the number of tires sold is a linear function of the amount of money invested in advertising. He randomly selects 6 months of data consisting of monthly tire sales (in thousands of tires) and monthly advertising expenditures (in thousands of dollars). Residuals are calculated for all of the randomly selected six months and ordered from smallest to largest. Determine the normal score for the smallest residual. A. .1053 B. 1.25 C. -1053 D. -1.25 AACSB: Analytic Bloom's: Application Difficulty: Easy Learning Objective: 9 Topic: Residual analysis 1-1271 Chapter 01 - An Introduction to Business Statistics 118. A local tire dealer wants to predict the number of tires sold each month. He believes that the number of tires sold is a linear function of the amount of money invested in advertising. He randomly selects 6 months of data consisting of monthly tire sales (in thousands of tires) and monthly advertising expenditures (in thousands of dollars). Residuals are calculated for all of the randomly selected six months and ordered from smallest to largest. Determine the normal score for the third residual in the ordered array. A. 0.421 B. -0.2 C. 0.2 D. -0.421 AACSB: Analytic Bloom's: Application Difficulty: Easy Learning Objective: 9 Topic: Residual analysis 1-1272 Chapter 01 - An Introduction to Business Statistics 119. A data set with 7 observations yielded the following. Use the simple linear regression model. = 21.57 = 68.31 = 188.9 = 5,140.23 = 590.83 SSE = 1.06 Find the estimated slope. A. 12.36 B. 3.13 C. 4.745 D. 8.70 AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 2 Topic: Simple Linear Regression 1-1273 Chapter 01 - An Introduction to Business Statistics 120. A data set with 7 observations yielded the following. Use the simple linear regression model. = 21.57 = 68.31 = 188.9 = 5,140.23 = 590.83 SSE = 1.06 Find the estimated y-intercept. A. 4.745 B. 12.36 C. 9.76 D. 3.08 AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 2 Topic: Simple Linear Regression 1-1274 Chapter 01 - An Introduction to Business Statistics 121. A data set with 7 observations yielded the following. Use the simple linear regression model. = 21.57 = 68.31 = 188.9 = 5,140.23 = 590.83 SSE = 1.06 Calculate the standard error. A. .212 B. .1514 C. .389 D. .4604 AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 3 Topic: Simple Linear Regression 1-1275 Chapter 01 - An Introduction to Business Statistics 122. A data set with 7 observations yielded the following. Use the simple linear regression model. = 21.57 = 68.31 = 188.9 = 5,140.23 = 590.83 SSE = 1.06 Find the rejection point for the t statistic ( A. 2.015, reject null hypothesis B. 13.993, reject null hypothesis C. 1.358, reject null hypothesis D. 36.460, reject null hypothesis = .05). Test H0: β1 ≤ 0 vs. Ha: β1 > 0. AACSB: Analytic Bloom's: Application Difficulty: Hard Learning Objective: 4 Topic: Significance of the slope 1-1276 Chapter 01 - An Introduction to Business Statistics 123. A data set with 7 observations yielded the following. Use the simple linear regression model. = 21.57 = 68.31 = 188.9 = 5,140.23 = 590.83 SSE = 1.06 Determine the 95% confidence interval for the average value of Y when x = 3.25. A. (27.31 28.25) B. (26.51 29.05) C. (1.98 4.52) D. (2.78 3.72) AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 5 Topic: Confidence & predication intervals 1-1277 Chapter 01 - An Introduction to Business Statistics 124. A data set with 7 observations yielded the following. Use the simple linear regression model. = 21.57 = 68.31 = 188.9 = 5,140.23 = 590.83 SSE = 1.06 Calculate the correlation coefficient. A. .111 B. .334 C. .974 D. .987 AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 6 Topic: Correlation 1-1278 Chapter 01 - An Introduction to Business Statistics 125. A data set with 7 observations yielded the following. Use the simple linear regression model. = 21.57 = 68.31 = 188.9 = 5,140.23 = 590.83 SSE = 1.06 Calculate the coefficient of determination. A. .111 B. .334 C. .974 D. .987 AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 6 Topic: Coefficient of determination 1-1279 Chapter 01 - An Introduction to Business Statistics 126. Use the least sq...
View Full Document

This document was uploaded on 01/20/2014.

Ask a homework question - tutors are online