6. The following inventory pattern has been observed in the Zahm Corporation over 12 months: Use both three-month and ?ve-month moving-average models to forecast the inventory for the next January. Use root-mean-squared error (RMSE) to evaluate these two forecasts. 11. a. Plot the data presented in Exercise 7 to examine the possible existence of trend and seasonality in the data. b. Prepare four separate smoothing models to examine the full-service restaurant sales data using the monthly data. 1. A simple smoothing model 2. Holts model 3. Winters model c. Examine the accuracy of each model by calculating the root-mean-squared error for each during the historical period. Explain carefully what characteristics of the original data led one of these models to minimize the root-mean-squared error. 13. The data in the table below are for retail sales in book stores by quarter. a. Plot these data and examine the plot. Does this view of the data suggest a particular smoothing model? Do the data appear to be seasonal? Explain. b. Use a smoothing method to forecast the next four quarters. Plot the actual and forecast values. **duplicate Figure 3.13 4. The following regression results relate to a study of the salaries of public school teachers in a midwestern city: a. What is the t-ratio for EXP? Does it indicate that experience is a statistically signi?cant determinant of salary if a 95 percent con?dence level is desired? b. What percentage of the variation in salary is explained by this model? c. Determine the point estimate of salary for a teacher with 20 years of experience. d. What is the approximate 95 percent con?dence interval for your point estimate from part (c)? 6. Mid-Valley Travel Agency (MVTA) has of?ces in 12 cities. The company believes that its monthly airline bookings are related to the mean income in those cities and has collected the following data: a. Develop a linear regression model of monthly airline bookings as a function of income. b. Use the process described in the chapter to evaluate your results. c. Make the point and approximate 95 percent con?dence interval estimates of monthly airline bookings for another city in which MVTA is considering opening a branch, given that income in that city is $39,020. 9. Carolina Wood Products, Inc., a major manufacturer of household furniture, is interested in predicting expenditures on furniture (FURN) for the entire United States. It has the following data by quarter for 1998 through 2007: a. Prepare a naive forecast for 2008Q1 based on the following model (see Chapter 1): b. Estimate the bivariate linear trend model for the data where TIME ? 1 for 1998Q1 through TIME ? 40 for 2007Q4. c. Write a paragraph in which you evaluate this model, with particular emphasis on its usefulness in forecasting. d. Prepare a time-trend forecast of furniture and household equipment expenditures for 2008 based on the model in part (b). e. Suppose that the actual values of FURN for 2008 were as shown in the following table. Calculate the RMSE for both of your forecasts and interpret the results. (For the naive forecast, there will be only one observation, for 2008Q1.) 10. Fifteen midwestern and mountain states have united in an effort to promote and forecast tourism. One aspect of their work has been related to the dollar amount spent per year on domestic travel (DTE) in each state. They have the following estimates for disposable personal income per capita (DPI) and DTE: a. From these data estimate a bivariate linear regression equation for domestic travel expenditures (DTE) as a function of disposable income per capita (DPI): Evaluate the statistical signi?cance of this model. b. Illinois, a bordering state, has asked that this model be used to forecast DTE for Illinois under the assumption that DPI will be $19,648. Make the appropriate point and approximate 95 percent interval estimates. c. Given that actual DTE turned out to be $7,754 (million), calculate the percentage e…
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