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Create an Excel spreadsheet on your own that can make combination forecasts for Problem 18. Create a combination forecast using all four techniques from Problem 18. Give each technique an equal weight. Create a second combination forecast by using the three techniques that seem best based on MAD. Give equal weight to each technique. Finally, create a third forecast by equally weighting the two best techniques. Calculate CFE, MAD, MSE, and MAPE for the combination forecast. Are these forecasts better or worse than the
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- Under what conditions might a firm use multiple forecasting methods?arrow_forwardThe 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.arrow_forwardThe 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?arrow_forward
- 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?arrow_forwardThe 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?arrow_forwardThe file P13_02.xlsx contains five years of monthly data on sales (number of units sold) for a particular company. The company suspects that except for random noise, its sales are growing by a constant percentage each month and will continue to do so for at least the near future. a. Explain briefly whether the plot of the series visually supports the companys suspicion. b. By what percentage are sales increasing each month? c. What is the MAPE for the forecast model in part b? In words, what does it measure? Considering its magnitude, does the model seem to be doing a good job? d. In words, how does the model make forecasts for future months? Specifically, given the forecast value for the last month in the data set, what simple arithmetic could you use to obtain forecasts for the next few months?arrow_forward
- It has been said that forecasting using exponential smoothing is like driving a car by looking in therear-view mirror. What are the conditions that would have to exist for driving a car that are analogous to the assumptions made when using exponential smoothing?2. What capability would an organization have to have to not need forecasts?3. When a new business is started, or a patent idea needs funding, venture capitalists or investmentbankers will want to see a business plan that includes forecast information related to a profit andloss statement. What type of forecasting information do you suppose would be required?4. Discuss how you would manage a poor forecast.5. Omar has heard from some of his customers that they will probably cut back on order sizes in thenext quarter. The company he works for has been reducing its sales force due to falling demand andhe worries that he could be next if his sales begin to fall off. Believing that he may be able to convince his customers not to cut…arrow_forwardDiscuss Qualitative forecasting technique. Explain the situations where we use Qualitative methods. Discuss Delphi forecasting method and its challenge.arrow_forwardUse the trend projection method, and the trend projection with seasonal adjustment method to create forecasting models in Excel. Next, using the two models, compute the forecasted values of monthly total passengers between 2010 to 2012 Compare the above two models using MAD, MSE, and MAPE Please explain which of the two models is performing better and why? Use the best model to forecast the monthly total passengers for year 2013arrow_forward
- The manager of a popular tourist resort wants to use the manual trend projection forecasting technique and exponential smoothing without trend to forecast room occupancy at the resort for the next 4 years. Using a numerical example, demonstrate how these techniques can be used to do the forecast. REQUIREMENT- USE EXPONENTIAL SMOOTHING(WITHOUT TREND) ONLYarrow_forwardThe past two years sales at ACSR Inc. were 3 million and 5 million. Their forecast team used a two-period moving average to forecast its sales this year. But the actual sales for this year were 5 million. Now, the forecast team wants to forecast its sales for next year by using exponential smoothing with alpha equals 0.6. What is the forecast using exponential smoothing with alpha = .6? 2. If we decide to use an alpha of .2 instead of .6, will we be ‘weighting the error from the previous period higher or the Forecast from the previous period higher? Explain briefly or show using math! (In this question I am asking if we change the alpha to a lower alpha, what will be the effect – what will we be ‘weighing’ as more important?)arrow_forwardThe number of fishing rods selling each day is given below. Perform analyses of the time series to determine which model should be used for forecasting. 3 day moving average analysis 4 day moving average analysis 3 day weighted moving average analysis with weights W1=0.2, W2=0.3 and W3=0.5 with W1 on the oldest data. Exponential smoothing analysis with A=0.3 Which model provides a better fit of the data? Forecast day 13 sales of fishing rods using the model chosen in part (e) Day Rods Sold 1 60 2 70 3 110 4 80 5 70 6 85 7 115 8 105 9 65 10 75 11 95 12 85 Please read the relevant article, found in the VLE, before answering the question. Discuss the process and findings of the study of the article. Suggest a possible study that could be done at your current or past job that could use a similar methodology and analysis.arrow_forward
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