Assume that you have three forecasting models. For the first, MAD = 2.5, for the second, the MSE =10.5 and for the thirds, MAPE = 2.7. On the basis of this information, which model is best? The second model. The third model. The first model. One cannot conclude.
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Assume that you have three
The second model.
The third model.
The first model.
One cannot conclude.
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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 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_26.xlsx contains the monthly number of airline tickets sold by the CareFree Travel Agency. a. Create a time series chart of the data. Based on what you see, which of the exponential smoothing models do you think will provide the best forecasting model? Why? b. Use simple exponential smoothing to forecast these data, using a smoothing constant of 0.1. c. Repeat part b, but search for the smoothing constant that makes RMSE as small as possible. Does it make much of an improvement over the model in part b?Lesson about Forecasting: Linear Regression and Measures of Variations, view the photo for details. Help me pls.
- Calculate the forecast for Week 16 using - a 2-period moving average - a 3-period moving average Compute MSE for the two models and compare the results and which model provides the best forecast?Freya is a new name in the retail industry that just started off its journey. With the right strategies, the brand’s grandeur will only rise with time. However, the founders really want to predict the customer demand right for the month of June. Hence, they need to figure out the right forecasting techniques. They are considering 2-period Moving Average, Naive technique, and Exponential Smoothing (use any value between .10 - .18 as the value of alpha). Figure out the better forecasting technique among 2 periods Moving Average, Naive technique, and Exponential Smoothing by doing the error calculation. Period Demand 2period Moving Average Naive technique Exponential Smoothing January 80 85 82 70 February 84 82 ** ** March 89 ** ** ** April 95 ** ** ** May 98 ** ** **At the ABC Floral Shop, an argument developed between two of the owners, Bob and Henry, over the accuracy of forecasting methods. Bob argued that exponential smoothing with α = .1 would be the best method. Henry argued that the shop would get a better forecast with α = .3.a. Using F1 = 100 and the data from problem 3, which of the two managers is right?b. Graph the two forecasts and the original data using Excel. What does the graph reveal?c. Maybe forecast accuracy could be improved. Try additional values of α = .2, .4, and .5 to see if better accuracy is achieved.
- Explain the term forecasting with least squares ?You have the following data: Actual Forecast 1 50 50 2 46 3 52 4 51 5 48 6 45 7 52 8 46 9 51 10 48 Compute the forecast using exponential smoothing with Using MSE, which of the above gives the best forecast of "Actual"? A) 0.8 B) 0.6 C) 0.4 D) 0.1 Note:- Do not provide handwritten solution. Maintain accuracy and quality in your answer. Take care of plagiarism. Answer completely. You will get up vote for sure.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…
