1-20chapter stats

The index is a weighted aggregate price index that

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: mple exponential smoothing and determined the following: S0 = 19, S1 = 18.6, S2 = 19.08, S3 = 19.064, S4 = 19.851 and S5 = 19.481. Calculate the Mean Absolute Deviation (MAD). A. 3.671 B. 8.215 C. 2.161 D. 1.643 AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 6 Topic: Exponential Smoothing 1-1621 Chapter 01 - An Introduction to Business Statistics 98. Consider the following data and calculate S1 using simple exponential smoothing and = 0.3. A. 19.14 B. 19.00 C. 18.40 D. 18.55 AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 5 Topic: Exponential Smoothing 1-1622 Chapter 01 - An Introduction to Business Statistics 99. Consider the following data and calculate S2 using simple exponential smoothing and α = 0.3. A. 18.40 B. 19.18 C. 19.00 D. 19.60 AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 5 Topic: Exponential Smoothing 1-1623 Chapter 01 - An Introduction to Business Statistics 100. Consider the following data and calculations. Calculate the estimated value of b1 and b0 and state the linear trend regression prediction equation. A. 2.5 + 1.43t B. 2.86 + 2.5t C. 1.43 + 2.5t D. 4.00 + 1.43t AACSB: Analytic Bloom's: Application Difficulty: Hard Learning Objective: 2 Topic: Time series regression 1-1624 Chapter 01 - An Introduction to Business Statistics 101. The linear trend equation for the following data is What is the predicted value of the fund in the period t = 1? A. 11.43 B. 3.93 C. 8.22 D. 2.50 AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 2 Topic: Time series regression 1-1625 Chapter 01 - An Introduction to Business Statistics 102. The linear trend equation for the following data is What is the predicted value of the fund in the period 7? A. 12.51 B. 48.93 C. 18.93 D. 29.67 AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 2 Topic: Time series regression 1-1626 Chapter 01 - An Introduction to Business Statistics 103. The linear trend equation for the following data is Find the residual value (error) for period 7. A. 6.49 B. -29.93 C. 0.07 D. -10.67 AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 2 Topic: Time series regression 1-1627 Chapter 01 - An Introduction to Business Statistics 104. Consider the regression equation = 6.04 + 0.10(t) and the data below. Compute the predicted value of sales for period 8. A. 48.42 B. 14.04 C. 6.75 D. 6.84 AACSB: Analytic Bloom's: Application Difficulty: Easy Learning Objective: 2 Topic: Time series regression 1-1628 Chapter 01 - An Introduction to Business Statistics 105. Consider the regression equation = 6.04 + 0.10(t) and the data below. Compute the residual (error term) for period 8. A. -1.25 B. -1.16 C. -0.35 D. -0.26 AACSB: Analytic Bloom's: Application Difficulty: Medium Learning Objective: 2 Topic: Time series regression 1-1629 Chapter 01 - An Introduction to Business Statistics Essay Questions 106. Consider the following set of quarterly sales data given in thousands of dollars. Write an appropriate dummy variable model that incorporates a linear trend and constant seasonal variation. y (t) = B0 + B1t + BQ1(Q1) + BQ2(Q2) + BQ3(Q3) + Et There are (4 - 1) = 3 binary seasonal variables (Q1, Q2, and Q3). Qi is a binary (0, 1) variable defined as: Qi = 1, if the time series data is associated with quarter i. Qi = 0, if the time series data is not associated with quarter i. y (t) = B0 + B1t + BQ1(Q1) + BQ2(Q2) + BQ3(Q3) + Et AACSB: Analytic Bloom's: Comprehension Difficulty: Hard Learning Objective: 2 Topic: Time series regression 1-1630 Chapter 01 - An Introduction to Business Statistics 107. Consider the following set of quarterly sales data given in thousands of dollars. The following dummy variable model that incorporates a linear trend and constant seasonal variation was used: y (t) = B0 + B1t + BQ1(Q1) + BQ2(Q2) + BQ3(Q3) + Et In this model there are 3 binary seasonal variables (Q1, Q2, and Q3). Where Qi is a binary (0, 1) variable defined as: Qi = 1, if the time series data is associated with quarter i; Qi = 0, if the time series data is not associated with quarter i. The results associated with this data and model are given in the following MINITAB computer output. The regression equation is Sales = 2442 + 6.2 Time - 693 Q1 - 1499 Q2 + 153 Q3 Provide a managerial interpretation of the regression coefficients for the variable "Q1" (quarter 1), "Q2" (quarter 2) and "Q3" (quarter 3). Excluding trend, estimated sales in quarter 1 (winter) is $693,000 less than the estimated sales in quarter 4 (fall). Excluding trend, estimated sales in quarter 2 (spring) is $1,499,000 less than the estimated sales in quarter 4 (fall). Excluding trend, estimated sales in quarter 3 (summer) is $153,000 more than the estimated sales in quarter 4 (fall). 1-1631 Chapter 01 - An Introduction to Business Statistics AACSB: Analytic Bloom's: Evaluation Difficulty: Hard Learning Objective: 2 Topi...
View Full Document

{[ snackBarMessage ]}

Ask a homework question - tutors are online