Question #2 Month Demand 1 45 2 48 3 43 4 48 5 49 6 54 7 47 8 50 9 46 10 47 Using the table above, calculate two forecasts using the following method:- First, for periods 4 through 10, develop the exponentially smoothed forecasts using a forecast for period 3 (F3) of 45.0 and an alpha of 0.4. ii. Calculate the weighted moving average for periods 4 through 10, using weights of .70, .20, and .10, with 0.70 applied to the most recent data. iii. Calculate the mean absolute deviation (MAD) for each forecasting procedure. Which forecasting procedure would you select? Why?

Question #2 Month Demand 1 45 2 48 3 43 4 48 5 49 6 54 7 47 8 50 9 46 10 47 Using the table above, calculate two forecasts using the following method:- First, for periods 4 through 10, develop the exponentially smoothed forecasts using a forecast for period 3 (F3) of 45.0 and an alpha of 0.4. ii. Calculate the weighted moving average for periods 4 through 10, using weights of .70, .20, and .10, with 0.70 applied to the most recent data. iii. Calculate the mean absolute deviation (MAD) for each forecasting procedure. Which forecasting procedure would you select? Why?

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section13.6: Moving Averages Models

Problem 22P: The file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six...

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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?
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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?
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Q3) Discuss Qualitative forecasting technique. Explain the situations where we use Qualitative methods. Discuss Delphi forecasting method and its challenge.
Q1) Forecasting is both art and science. Describe the situations where we use Qualitative forecasting techniques and quantitative forecasting techniques
FORECASTING- EXPONENTIAL SMOOTHING QUESTION 3 PERIOD АCTUAL 1 42 2 40 3 43 4 40 5 41 39 7 46 8 44 9. 45 10 38 11 40 12 a) Consider exponential smoothing forecasts using smoothing constants (a) 0.1 and 0.4
14 Community General Hospital finds itself treating many bicycle accident victims. Data from the last seven 24-hour periods is shown below: Day Bicycle Victims 1 8 2 14 3 8 4 14 5 18 6 15 With an alpha value of 0.31 and a starting forecast in day 3 equal to the 21 , what is the exponentially smoothed forecast for day 4? (Round to two decimal places) 15 What is the exponentially smoothed forecast for day 5? (Round to two decimal places)
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Tools View Week 3 Bonus Activity- DEMAND FORECASTING CASE STUDY After reviewing the forecasting demonstration and looking over the slides, complete the following case activity and transfer your answers to the appropriate questions in the Canvas activity quiz. You have been hired as a demand planning intern for Hawaiian Island Creations (HIC). They want you to de- velop a forecast for their HIC Papanui style of sun- glasses. The goal is to determine how many pair they will produce to meet retailer demand in July 2021. During your first meeting, you were handed some data to work with and the product team talked about the company's upcoming promotional blitz to support Summer Break '21 in major vacation destinations. Month Forecast Demand January 2021 4.000 3,300 February 2021 4,200 3,900 March 2021 4,500 4,300 April 2021 4.800 4,200 May 2021 5 000 5.400 of 4 P Type here to search 立