The data shown in the following table represent visitors to the Hawaiian Islands over the past several years, by quarter. Use the data for the first five years to estimate the seasonal and trend factors. Then build an exponential smoothing model (incorporating both trend and seasonal factors) to provide for the forecasts of the remaining periods. Plot the actual visitors and the forecasts. Compare the accuracy of the forecasts in the 1985 to 1990 period with those subsequent to that period.
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- Under what conditions might a firm use multiple forecasting methods?The file P13_42.xlsx contains monthly data on consumer revolving credit (in millions of dollars) through credit unions. a. Use these data to forecast consumer revolving credit through credit unions for the next 12 months. Do it in two ways. First, fit an exponential trend to the series. Second, use Holts method with optimized smoothing constants. b. Which of these two methods appears to provide the best forecasts? Answer by comparing their MAPE values.The owner of a restaurant in Bloomington, Indiana, has recorded sales data for the past 19 years. He has also recorded data on potentially relevant variables. The data are listed in the file P13_17.xlsx. a. Estimate a simple regression equation involving annual sales (the dependent variable) and the size of the population residing within 10 miles of the restaurant (the explanatory variable). Interpret R-square for this regression. b. Add another explanatory variableannual advertising expendituresto the regression equation in part a. Estimate and interpret this expanded equation. How does the R-square value for this multiple regression equation compare to that of the simple regression equation estimated in part a? Explain any difference between the two R-square values. How can you use the adjusted R-squares for a comparison of the two equations? c. Add one more explanatory variable to the multiple regression equation estimated in part b. In particular, estimate and interpret the coefficients of a multiple regression equation that includes the previous years advertising expenditure. How does the inclusion of this third explanatory variable affect the R-square, compared to the corresponding values for the equation of part b? Explain any changes in this value. What does the adjusted R-square for the new equation tell you?
- The file P13_29.xlsx contains monthly time series data for total U.S. retail sales of building materials (which includes retail sales of building materials, hardware and garden supply stores, and mobile home dealers). a. Is seasonality present in these data? If so, characterize the seasonality pattern. b. Use Winters method to forecast this series with smoothing constants = = 0.1 and = 0.3. Does the forecast series seem to track the seasonal pattern well? What are your forecasts for the next 12 months?The Baker Company wants to develop a budget to predict how overhead costs vary with activity levels. Management is trying to decide whether direct labor hours (DLH) or units produced is the better measure of activity for the firm. Monthly data for the preceding 24 months appear in the file P13_40.xlsx. Use regression analysis to determine which measure, DLH or Units (or both), should be used for the budget. How would the regression equation be used to obtain the budget for the firms overhead costs?The file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six months of observations for validation purposes, use the method of moving averages with a carefully chosen span to forecast U.S. retail sales in the next year. Comment on the performance of your model. What makes this time series more challenging to forecast?
- A company executive is trying to choose between two methods of forecasting sales that he has been using during the past five months. The values are as shown below. Forecast Month Method 1 Method 2 Actual Sales 1 5324 5208 5582 2 5405 5377 4906 3 5195 5462 5755 4 5511 5414 6320 5 5762 5549 5153 Calculate and compare MAD and MSE for these two methods.Alvin Cheah is a marketing analyst for Rockstar Travel Company. He wants to analyze the trend ofinternational tourist arrival in Tawau by using international tourist arrival rate and flight delayed rate overthe past 10 years as given in Table 2 below: (Hint: Provides your answers in two decimal points) (i) Propose ONE (1) forecasting model that can be used by Alvin. Why would you proposed that particular model?(ii) Develop the forecasting model that you suggest in (i). Briefly explain your model.Consider the following time series data. Month 1 2 3 4 5 6 7 Value 24 13 20 12 19 23 15 Compute MSE using the most recent value as the forecast for the next period. What is the forecast for month 8? Compute MSE using the average of all the date available as the forecast for the next period. What is the forecast for month 8? Which method appears to provide the better forecast?
- The manager of a utility company in the Texas panhandlewants to develop quarterly forecasts of power loads for the nextyear. The power loads are seasonal, and the data on the quar-terly loads in megawatts (MW) for the last 4 years are as follows: The manager estimates the total demand for the next year at600 MW. Use the multiplicative seasonal method to developthe forecast for each quarter.Alvin Cheah is a marketing analyst for Rockstar Travel Company. He wants to analyze the trend of international tourist arrival in Tawau by using international tourist arrival rate and flight delayed rate over the past 10 years as given in Table 2 below: (Hint: Provides your answers in two decimal points) (i) Propose ONE (1) forecasting model that can be used by Alvin. Why would you proposed that particular model? (ii) Develop the forecasting model that you suggest in (i). Briefly explain your model.Air travel on Mountain Airlines for the past 18 weeks was:Week Passengers1 4052 4103 4204 4155 4126 4207 4248 4339 43810 44011 44612 45113 45514 46415 46616 47417 47618 482a. Explain why an averaging technique would not be appropriate for forecasting.b. Use an appropriate technique to develop a forecast for the expected number of passengers forthe next three weeks.