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9982 9263 1139 9365 for winter spring summer and fall

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Unformatted text preview: s most accurate because it has the smallest MAD and MSD. AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 8 Topic: Exponential modeling 139. Listed below are the price of a pair of men's boots over a 50 year time period. Find the simple index numbers for the data with 1950 as the base year. 100.0, 144.0, 200, 310.7, 356.6, 388.8 AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 9 Topic: Index numbers 1-1654 Chapter 01 - An Introduction to Business Statistics 140. Using the price of the following food items, compute the aggregate index numbers for the four type of cheeses. Let 1990 be the base year for this market basket of goods. 100.0, 108.5, 112.0 Totals: 8.33, 9.04, 9.33 Index: 8.33/8.33; 9.04/8.33; 9.33/8.33 AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 9 Topic: Index numbers 141. The price and quantity of several food items are listed below for the years 1990 and 2000. Compute the Laspeyres index using 1990 as the base year. 110.35 AACSB: Analytic Bloom's: Application Difficulty: Hard Learning Objective: 9 Topic: Index numbers 1-1655 Chapter 01 - An Introduction to Business Statistics 142. The price and quantity of several food items are listed below for the years 1990 and 2000. Compute the Paasche index using 1990 as the base year. 179.73 AACSB: Analytic Bloom's: Application Difficulty: Hard Learning Objective: 9 Topic: Index numbers 1-1656 Chapter 01 - An Introduction to Business Statistics 143. Given the following data Compute the total error (sum of the error terms) 22.896 AACSB: Analytic Bloom's: Application Difficulty: Easy Learning Objective: 6 Topic: Forecasting 1-1657 Chapter 01 - An Introduction to Business Statistics 144. Given the following data Compute the mean squared deviation (error) 34.205 AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 6 Topic: Exponential Smoothing 1-1658 Chapter 01 - An Introduction to Business Statistics 145. Given the following data Compute the mean absolute deviation. 4.607 AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 6 Topic: Exponential Smoothing 1-1659 Chapter 01 - An Introduction to Business Statistics 146. Consider the regression equation and the data below: Compute the predicted value for sales for period 6 and 7. 40.893, 44.655 AACSB: Analytic Bloom's: Application Difficulty: Easy Learning Objective: 2 Topic: Time series regression 1-1660 Chapter 01 - An Introduction to Business Statistics 147. Consider the regression equation and the data below: Compute the residuals (error terms) for period 6 and 7. 6.107, .345 e6 = 47 - 40.893 = 6.107 e7 = 45 - 44.655 = .345 AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 2 Topic: Time series regression 148. The linear regression trend model was applied to a time series of sales data based on the last 16 months of sales. The following partial computer output was obtained: Write the prediction equation. y = 18.100 + 3.2456(t) AACSB: Analytic Bloom's: Comprehension Difficulty: Easy Learning Objective: 2 Topic: Time series regression 1-1661 Chapter 01 - An Introduction to Business Statistics 149. The linear regression trend model was applied to a time series of sales data based on the last 16 months of sales. The following partial computer output was obtained: Test the significance of the time term at α = .05. State the critical t value and make your decision using a two-sided alternative. t = 7.71, reject Ho t.025,14 = 2.145 7.71 > 2.145, reject Ho It appears that time variable significantly affects sales. AACSB: Analytic Bloom's: Comprehension Difficulty: Medium Learning Objective: 2 Topic: Time series regression 150. The linear regression trend model was applied to a time series of sales data based on the last 16 months of sales. The following partial computer output was obtained: What is the predicted value of y when t = 17? 73.3752 AACSB: Analytic Bloom's: Application Difficulty: Easy Learning Objective: 2 Topic: Time series regression Chapter 17 Process Improvement Using Control Charts True / False Questions 1-1662 Chapter 01 - An Introduction to Business Statistics 1. A control chart is a graph whose purpose is to detect assignable causes of variation in a process. True False 2. An chart is a control chart on which individual process measurements are plotted versus time. True False 3. A range chart is a control chart in which ranges between individual process measurements within subgroup are plotted. True False 4. A p-chart is a control chart on which the proportions of nonconforming units are plotted versus time. True False 5. Process leeway is the distance between natural tolerance limits and control limits. True False 6. Periodic sampling is observing the output of a process at random intervals. True False 1-1663 Chapter 01 - An Introduction to Business Statistics 7. Sigma level capability is the number of estimated process standard deviations...
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