1-20chapter stats

A index b cycle c seasonal d irregular 1 1538 chapter

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Unformatted text preview: d 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 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 1-1550 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. 29.67 103. 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 1-1551 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 1-1552 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 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. 1-1553 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). 1-1554 Chapter 01 - An Introduction to Business Statistics 108. 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 coefficient for the variable "time." 1-1555 Chapter 01 - An Introduction to Business Statistics 109. 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 At α = .05, test the significance of the model. 1-1556 Chapter 01 - An Introduction to Business Statistics 110. The linear regression trend model was applied to a time series sales data based on the last 24 months' sales. The following partial computer output was obtained. Write the prediction equation. 111. The linear regression trend model was applied to a time series sales data based on the last 24 months' 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. 112. The linear regression trend model was applied to a time series sales data based on the last 24 months' sales. The following partial computer output was obtained. What is the predicted value of y when t = 25? 1-1557 Chapter 01 - An Introduction to Business Statistics 113. Consider a time series with 15 quarterly sales observations. Using the quadratic trend model the following partial computer output was obtained. Write the prediction equation. 114. Consider a time series with 15 quarterly sales observations. Using the quadratic trend model the following partial computer output was obtained. State the two-sided null and alternative hypothesis to test...
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