a) The demand forecast for Month 6 would be: A. 565 haircuts B. 574 haircuts C. 578 haircuts D. 584 haircuts b) With Mean Absolute Deviation (MAD) as the criterion, the best forecasting model for this time series data is: A. Naïve approach B. 2-week Simple Moving Average (SMA) C. Weighted Moving Average (WMA) with weights: 0.5, 0.3, 0.2 D. Exponential Smoothing (ES) with alpha = 0.8 TIME SERIES FORECASTINGDemand for haircut at PogiPoints Barber Shop has increased steadily for the pastfew months as seen in the following time series data. Do the necessarycomputations and choose the best answer that would complete each statement.NASMA; n= 2WMA; 0.2, 0.3, 0.5ES; a = 0.8MONTHHAIRCUTS PERFORMED|A-F||A-F||A-F||A-F|FFFF14502495352045635846.

a) The demand forecast for Month 6 would be: A. 565 haircuts B. 574 haircuts C. 578 haircuts D. 584 haircuts b) With Mean Absolute Deviation (MAD) as the criterion, the best forecasting model for this time series data is: A. Naïve approach B. 2-week Simple Moving Average (SMA) C. Weighted Moving Average (WMA) with weights: 0.5, 0.3, 0.2 D. Exponential Smoothing (ES) with alpha = 0.8

a) The demand forecast for Month 6 would be: A. 565 haircuts B. 574 haircuts C. 578 haircuts D. 584 haircuts b) With Mean Absolute Deviation (MAD) as the criterion, the best forecasting model for this time series data is: A. Naïve approach B. 2-week Simple Moving Average (SMA) C. Weighted Moving Average (WMA) with weights: 0.5, 0.3, 0.2 D. Exponential Smoothing (ES) with alpha = 0.8

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section: Chapter Questions

Problem 42P: The file P13_42.xlsx contains monthly data on consumer revolving credit (in millions of dollars)...

See similar textbooks

Similar questions

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?
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 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?
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…
Holiday Lodge The Holiday Lodge is a large hotel and casino in the Adirondacks. The relatively new hotel is two years old, and the manager is trying to develop a plan to staff the maintenance department. The hotel’s manager wants to use the two years of data below to forecast one month ahead of maintenance calls. The data is provided in the spreadsheet named HOLIDAY LODGE DATA.XLS Month Calls 1 46 2 39 3 28 4 21 5 14 6 16 7 14 8 13 9 9 10 13 11 18 12 15 13 12 14 6 15 19 16 9 17 12 18 14 19 16 20 12 21 13 22 9 23 14 24 15 Develop a forecast for month 25 using a 4 month moving average, exponential smoothing (a = 0.2) and regression. Which forecast is preferred? Why?
What should be our forecast accuracy target if there is a high degree of volatility in customer orders and long lead times? We have a new chief sales officer who is proposing that we should forecast in dollars, not in units/cases. I have never heard of anyone forecasting in dollars. It is true that dollarized forecasts can help Sales in knowing precisely what sales target they should be hitting. But, is it the best practice?
The number of heart surgeries performed at HeartvilleGeneral Hospital has increased steadily over the past sev-eral years. The hospital’s administration is seeking the bestmethod to forecast the demand for such surgeries in year 6.The data for the past 5 years are shown. The hospital’s administration is considering the followingforecasting methods. Begin error measurement in year 3 soall methods are compared for the same years.i. Exponential smoothing, with a = 0.6. Let the initial fore-cast for year 1 be 45, the same as the actual demand.ii. Exponential smoothing, with a = 0.9. Let the initial fore-cast for year 1 be 45, the same as the actual demand.iii. Trend projection with regression.iv. Two-year moving average.v. Two-year weighted moving average, using weights 0.6 and0.4, with more recent data given more weight.vi. If MAD is the performance criterion chosen by the admin-istration, which forecasting method should it choose?vii. If MSE is the performance criterion chosen by the…
Clinic administrator Marc Schniederjans wants you to forecastpatient demand at the clinic for week 7 by using this data. You decide to use a weighted moving average method to find this fore-cast. Your method uses four actual demand levels, with weights of 0.333 on the present period, 0.25 one period ago, 0.25 two peri-ods ago, and 0.167 three periods ago. a) What is the value of your forecast? PXb) If instead the weights were 20, 15, 15, and 10, respectively, howwould the forecast change? Explain why. c) What if the weights were 0.40, 0.30, 0.20, and 0.10, respec-tively? Now what is the forecast for week 7?
The following two demand sets are to be used to test two different basic exponential smoothingmodels. The first model uses 0.1, and the second uses 0.5. In both cases, the modelshould be initialized with a beginning forecast value of 50; that is, the ESF forecast for period 1made at the end of period 0 is 50 units. In each of the four cases (two models on two demandsets), compute the average forecast error and MAD. What do the results mean?Demand Set I Demand Set IIPeriod Demand Period Demand1 51 1772 46 2833 49 3904 55 4225 52 5106 47 6807 51 7168 48 8199 56 92710 51 10 7911 45 11 7312 52 12 8813 49 13 1514 48 14 2115 43 15 8516 46 16 2217 55 17 8818 53 18 7519 54 19 1420 49 20 16
Lesson about Forecasting: Linear Regression and Measures of Variations, view the photo for details. Help me pls.