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A multiple regression model is used to compare the

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Unformatted text preview: the multiple regression equation is equal to 114.7. The computer output also shows that MSE is equal to 144 and the leverage value is 0.19. Calculate the adjusted R2 where R2 = . 716, the number of observations is 20, and the number of independent variables is 2. .683 AACSB: Analytical Skills Bloom's: Application Difficulty: Medium Learning Objective: 5 Topic: Model Building 1-1513 Chapter 01 - An Introduction to Business Statistics 95. In a multiple regression model with 4 independent variables and 25 observations, an observation's actual y value is 128.2, and the predicted value of the dependent variable based on the multiple regression equation is equal to 114.7. The computer output also shows that MSE is equal to 144 and the leverage value is 0.19. Calculate the Cook's D statistic for this observation. Based on the Cook's statistic value is this observation influential? Why? 0.0733. No, this observation is not influential because .0733 < 1 AACSB: Analytical Skills Bloom's: Application Difficulty: Hard Learning Objective: 5 Topic: Outliers & Influential Observations 1-1514 Chapter 01 - An Introduction to Business Statistics 96. The following time sequenced observations of actual and predicted values of the dependent variable (demand) are obtained from a multiple regression model with 3 independent variables. Determine the Durbin-Watson statistic (d). 1.889 AACSB: Analytical Skills Bloom's: Application Difficulty: Medium Learning Objective: 8 Topic: Autocorrelation 1-1515 Chapter 01 - An Introduction to Business Statistics 97. Based on 25 time ordered observations from a multiple regression model with 3 independent variables, we have determined the Durbin-Watson statistic, d = 1.29. At α = .05, test to determine if there is any evidence of positive autocorrelation? State your conclusions. No because 1.12 < 1.29 < 1.66. The test results are inconclusive. AACSB: Analytical Skills Bloom's: Application Difficulty: Medium Learning Objective: 8 Topic: Autocorrelation 98. Based on 30 time ordered observations from a multiple regression model with 2 independent variables, we have determined the Durbin-Watson statistic, d = 2.71. At α = .05, test to determine if there is any evidence of negative autocorrelation? State your conclusions. Yes, there is evidence of negative autocorrelation because 2.71 > 2.65. AACSB: Analytical Skills Bloom's: Application Difficulty: Medium Learning Objective: 8 Topic: Autocorrelation 1-1516 Chapter 01 - An Introduction to Business Statistics 99. A multiple regression model was applied to a data set with 8 time ordered observations. The residuals for these observations are given below. Calculate the value of MSE and the standard error. 0.4719, .6869 AACSB: Analytical Skills Bloom's: Application Difficulty: Medium Learning Objective: 5 Topic: Model Building 1-1517 Chapter 01 - An Introduction to Business Statistics 100. A multiple regression model was applied to a data set with 8 time ordered observations. The residuals for these observations are given below. Calculate the Durbin-Watson statistic (d). 2.055 AACSB: Analytical Skills Bloom's: Application Difficulty: Medium Learning Objective: 8 Topic: Autocorrelation 1-1518 Chapter 01 - An Introduction to Business Statistics 101. A multiple regression model with 3 independent variables and 16 observations produced the following analysis of variance table. After some consideration, the analyst decided to add two new independent variables to the multiple regression model. As a result of this change, the unexplained variation (SSE) decreased by 5. Complete the new analysis of variance table after the addition of the two new independent variables. Did the two newly added variables improve the model? No. The F value decreased from 8 to 7. AACSB: Analytical Skills Bloom's: Application Difficulty: Hard Learning Objective: 5 Topic: Model Building 102. Use the following correlation matrix and determine the best multiple regression prediction equation that has no significant multicollinearity. AACSB: Analytical Skills Bloom's: Application Difficulty: Hard Learning Objective: 4 Topic: Multicollinearity Chapter 16 Time Series Forecasting 1-1519 Chapter 01 - An Introduction to Business Statistics True / False Questions 1. A univariate time series model is used to predict future values of a time series based only upon past values of a time series. True False 2. Trend refers to a long-run upward or downward movement of a time series over a period of time. True False 3. Exponential smoothing is a forecasting method that applies equal weights to the time series observations. True False 4. The smoothing constant is a number that determines how much weight it is attached to each observation. True False 5. Simple exponential smoothing is an appropriate method for prediction purposes when there is a significant trend present in a time series data. True False 6. The forecaster who uses MSD (mean squared deviations) to measure the effectiveness of forecasting metho...
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This document was uploaded on 01/20/2014.

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