Income at the law firm of Smith and Jones for the period February to July was as follows: February 75.0 March 71.5 Month Income (in $ thousand) April 66.4 May 72.3 June July 73.5 74.0 Assume that the initial forecast for February is $70,000 and the initial trend adjustment is 0. The smoothing constants selected are a=0.2 and B=0.2. Using trend-adjusted exponential smoothing, the forecast for the law firm's August income = thousand dollars (round your response to two decimal places). The mean squared error (MSE) for the forecast developed using trend-adjusted exponential smoothing = (thousand dollars) (round your response to two decim places).
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- Under what conditions might a firm use multiple forecasting methods?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 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_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 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?Income at the law firm of Smith and Jones for the period February to July was as follows: Month February March April May June July Income (in $ thousand) 90.0 91.5 96.0 85.4 92.2 96.0 Assume that the initial forecast for February is $85,000 and the initial trend adjustment is 0. The smoothing constants selected are a = 0.1 and ß = 0.2. Using trend-adjusted exponential smoothing, the forecast for the law firm's August income =O thousand dollars (round your response to two decimal places).
- Income at the architectural firm of Spraggins and Yunes for the period February to July was as follows: Month Income ($000's) February March 70.0 68.5 The mean squared error (MSE) for the forecast developed using trend-adjusted exponential smoothing = April 64.8 May 71.7 June 71.3 July 72.8 Assume that the initial forecast for February is 65.0 (in $ thousands) and the initial trend adjustment is 0. The smoothing constants selected are α = 0.10 and ß = 0.2. Using trend-adjusted exponential smoothing, the forecast for the architectural firm's August income = thousand dollars (round your response to two decimal places). (thousand dollars)² (round your response to two decimal places).Income at the architectural firm Spraggins and Yunes for the period February to July was as follows: February April May Month Income ($000's) 35.0 28.1 26.3 March 32.6 June 34.5 July 32.0 Assume that the initial forecast for February is 30.0 (in $ thousands) and the initial trend adjustment is 0. The smoothing constants selected are α = 0.1 and ß = 0.3. Using trend-adjusted exponential smoothing, the forecast for the architectural firm's August income is thousand dollars (round your response to two decimal places).Income at the architectural firm Spraggins and Yunes for the period February to July was as follows: ...4.19 FEBRUARY MARCH APRIL MAY JUNE JULY 64.8 71.7 71.3 72.8 MONTH Income (in $ thousand) 70.0 68.5 Use trend-adjusted exponential smoothing to forecast the firm's August income. Assume that the initial forecast average for February is $65,000 and the initial trend adjustment is 0. The smoothing constants selected are a = .1 and 3 = .2. Px ...4.20 Resolve Problem 4.19 with a = .1 and 3 = .8. Using MSE, determine which smoothing constants provide a better forecast. PX
- 12.7 The Intrepid mutual fund of growth stocks has had the following average monthly price for the past 10 months. Month 1 2 3 4 5 6 7 8 9 10 Fund Price 62.7 63.9 68.0 66.4 67.2 65.8 68.2 69.3 67.2 70.1 Compute the exponentially smoothed forecast with a = 0.40, the adjusted exponentially smoothed forecast with a = 0.40 and ß = 0.30, and the linear trend line forecast. Compare the accuracy of the three forecasts using cumulative error and MAD, and indicate which forecast appears to be most accurate.Income at the architectural firm Spraggins andYunes for the period February to July was as follows: Use trend-adjusted exponential smoothing to forecast thefirm’s August income. Assume that the initial forecast averagefor February is $65,000 and the initial trend adjustmentis 0. The smoothing constants selected are a = .1 andb = .2.Calanute Beach Resort, a fictional seaside luxury hotelin Goa, India, had the following occupancy rates for 12months in 2014Month Occupancy Rate in %1 652 683 724 755 786 837 928 889 7610 6511 6412 69a Forecast the occupancy rate for January2015 usingsimple exponential smoothing with α = 0.4. Assumethat the forecast for Month 2 (F2) is 65%. b Forecast the January 2015 occupancy rate usingtrend-adjusted simple exponential smoothing with α =…