3. National Mixer, Inc., sells can openers. Monthly sales for a seven-month period wereas follows: ,SalesMonth(000 units)Feb.19Mar.181520182220Apr.MayJun.Jul.Aug.a. Plot the monthly data on a sheet of graph paper.b. Forecast September sales volume using each of the following:(1) A linear trend equation.(2) A five-month moving average.(3) Exponential smoothing with a smoothing constant equal to .20, assuming a Marchforecast of 19,000.(4) The naive approach.(5) A weighted average using .60 for August, .30 for July, and .10 for June.Which method seems least appropriate? Why?d. What does use of the term sales rather than demand presume?C....

Note: - Since we can answer only up to three subparts we will answer the first three subparts (a, b…

Answered: 3. National Mixer, Inc., sells can…

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)...

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Similar questions

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.
Consider the following sales data for Bell, Inc. Month Sales ($ Millions) Jan. 10 Feb. 12 March 14 April 16 May 18 June 23 July 26 Aug. 31 Sept. 27 Oct. 18 Nov. 16 Dec. 14 a. Use a three-month weighted moving average to forecast the sales for the months April through December. Use weights of (3/6), (2/6), and (1/6), giving more weight to more recent data. b. Use exponential smoothing with α = 0.30 to forecast the sales for the months April through December. The forecast for January was $12 million. c. Compare the performance of the two methods by using the bias and MAD as the performance criteria. Which performance method is the most reasonable? Why?
3. The following tabulations are actual sales of units for 6 months and a starting forecast in January. a. Calculate forecasts for the remaining 5 months using simple exponential smoothing with a = 0.2. b. Calculate MAD for the forecasts. January February March April May June Actual 100 94 106 80 68 94 Forecast 80
4. The sales (in millions of dollars) for a 15-month period are as follows. Month Sales Month Sales 390 9 470 2 565 10 1000 3 395 11 490 450 12 485 490 13 525 560 14 550 7 420 15 530 8. 565 a. Compare a three-month moving average forecast with an exponential smoothing forecast. Use a = 0.2. Find MSE for both methods. b. Which provides the better forecasts based on MSE? C. Find the forecast for the next month using the best forecast method. 5.
B). Using exponential smoothing, calculate the forecasts for months 2, 3, 4, 5, and 6. The smoothing constant is 0.2, and the old forecast for month I is 245. Month Actual Demand Forecast Demand 1 260 2. 230 3 225 4 245 5 250 6. C). Given the following average demand for each month, calculate the seasonal indices for each month. Month Average Demand Seasonal Index January 30 February 50 March 85 April 110 May 125 June 245 July 255 August 135 September 100 October 90 November 50 December 30 Total 3 D). Using the data in part A and the seasonal indices you have calculated, calculate expected monthly demand if the annual forecast is 2000 units. Month Seasonal Forecast Index January February March April May June July August September October November December
22. Handy, Inc., produces a solar-powered electronic calculator that has experienced the following monthly sales history for the first four months of the year, in thousands of units: 23.3 March January February 30.3 72.3 April 15.5 a. If the forecast for January was 25, determine the one-step-ahead forecasts for February through May using exponential smoothing with a smoothing con- stant of a = .15. b. Repeat the calculation in part (a) for a value of a forecasts do you observe? c. Compute the MSES for the forecasts you obtained in parts (a) and (b) for February through April. Which value of a gave more accurate forecasts, based on the MSE? .40. What difference in the
Handy, Inc., produces a solar-powered electronic calculator that has experiencedthe following monthly sales history for the first four months of the year, inthousands of units:January 23.3 March 30.3February 72.3 April 15.5a. If the forecast for January was 25, determine the one-step-ahead forecasts forFebruary through May using exponential smoothing with a smoothing constant of a=.15.b. Repeat the calculation in part (a) for a value of a= .40. What difference in theforecasts do you observe?c. Compute the MSEs for the forecasts you obtained in parts (a) and (b) forFebruary through April. Which value of a gave more accurate forecasts, basedon the MSE?
National Mixer, Inc., sells can openers. Monthly sales for a seven-month period were as follows: Month Sales (000 units) Feb 19 Mar 18 Apr May 15 20 Jun 18 July Aug. 22 20
a. Identify and give a brief explanation of the:i. Dependent variableii. Independent variable b. Use simple linear regression to forecast annual demand for months 9 and 10 by using thetabular method to:i. Derive the values for the intercept and slope. ii. Derive the linear regression equation.iii. Plot the linear regression line. iv. Develop a forecast of the clinic attendance for months 9 and 10.
b. Prepare forecasts for June through September by using an exponential smoothing model with α = 0.4. Assume that the forecast for May was 2,100 (enter your responses rounded to the nearest whole number). Month March April May June July August September March April May June Demand Demand 120 2,030 1,110 4,210 3,260 5,830 c. Prepare forecasts for June through September by using an adjusted exponential smoothing model with α = 0.4 and ß = 0.2. Assume that the unadjusted forecast for May was 2,100 and the trend factor T₁ for May was 900 (enter your responses rounded to the nearest whole number). Month 120 2,030 1,110 4,210 Forecast 2,100 1704 2707 2928 4089 2,100 1,704 Unadjusted forecast Adjusted forecast
17. Statistical and observational methods, where adequate data or settings are available in which to apply them, are superior to survey methods of forecasting. Select one O True O False

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