Based on above assume you are using the moving average forecasting method based on the last four observations. When making the forecast for the last period, theoldest of the four observations was 1945 and the forecast was 2083. Thetrue value for the last period then turned out to be 1977. Calculate yourforecast for the next period. Can you show on excel?
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Based on above assume you are using the moving average forecasting method based on the last four observations. When making the forecast for the last period, the
oldest of the four observations was 1945 and the forecast was 2083. The
true value for the last period then turned out to be 1977. Calculate your
forecast for the next period. Can you show on excel?
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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 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_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 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?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?
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- If the forecasted demand for the week of August 31 is 360 and α = 0.20, using exponential smoothing, develop the forecast for each of the weeks with the known demand and the forecast for the week of October 12 (round your responses to two decimal places). Week Of Pints Used Forecast for this Date August 31 360 360 September 7 389 360.00 September 14 412 365.80 September 21 383 375.04375.04 SeptemberYou discovered that the forecasting error falls beyond the acceptable ranges in the past three years. Make a reliable forecast for the demand on your product/service using at least 10 periods of your historical data to forecast the demand for the coming 5 periods. Then compute the MAD for these 5 periods . Period Actual (A) Forecast (F) (A-F) Error 1 107 110 -3 2 125 121 4 3 115 112 3 4 118 120 -2 5 108 109 1 6 118 120 -2 7 108 109 1 8 115 112 -3 9 140 137 -3 10 106 102 -4The manager of a travel agency asked you to come up with a forecasting technique that will best fit to the actual demand for packaged tours. You have observed and recorded the actual demand for the last 10 periods. You also identified two possible techniques for consideration: 2-month moving averages (F1), and exponential smoothing (F2) with a smoothing constant of 0.25. Using Cumulative Forecasting Error (CFE) and Mean Absolute Deviation (MAD) as your performance measures you will determine the technique that will best fit to the actual demand data provided in the following table.STEP 1: Given start forecast values in period 3, compute forecast values from period 4 to 10. You are asked to provide the forecast values for period 6 and 10 for both techniques. 2-Month MA Exponential Period Demand F1 F2 1 115 -- -- 2 176 -- -- 3 97 146 129 4 141 5 98 6 132 7 114 8 129 9 107…