6. Tread-On-Us Carpet & Tile Company sold 700,000 square f.et of carpet last year,800,000 square feet the year before, and 600,000 squarea. Using a three-year moving average, predict carpet sales for this year.b. Then, assuming actual sales for this year turn out to be 780,000 square feet, predictsales for next year.feet theyearbefore that.

Moving average is a method of forecasting. It is calculated by adding up all the data points of a…

Answered: 6. Tread-On-Us Carpet & Tile Company…

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter2: Introduction To Spreadsheet Modeling

Section: Chapter Questions

Problem 20P: Julie James is opening a lemonade stand. She believes the fixed cost per week of running the stand...

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3. National Mixer, Inc., sells can openers. Monthly sales for a seven-month period were as follows: , Sales Month (000 units) Feb. 19 Mar. 18 15 20 18 22 20 Apr. May Jun. 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 March forecast 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. ...
Al Maha Plastic manufacturing Companies last Six weekly values of Sales were 90, 110, 115, 135, 140, 150 and 160 units. Forecasts (same for all the six weeks) were 110 units for all the weeks. Calculate MAD, and Tracking Signal for these six weeks. Wee k Actual Sales Forecaste d Sale Error Cumulative Error Absolute Error Cumulative Absolute Error MAD Tracking Signal 1 2 3 4 5 6 7
*** Can you please demonstrate how to do parts d, e, f? Given: Year Demand 1 7 2 9 3 5 4 9 5 Predict the value for Year 5: 2 year moving average What is MSE for 2 year moving average? 2 year moving average using 0.6 (weight for the oldest period) and 0.4(weight for most recent period Exponential smoothing, =0.2 and forecast for Year 1 = 5 Linear trend Which forecast method has the least amount of error using MAD? What is the coefficient?
2-1 Sales of Cool-Man air conditioners have grown steadily during the past 5 years: DEMAND ADV SEPENT 2017 450 1200 2018 495 1650 2019 518 1710 2020 563 1860 2021 584 1960 Predict the demand of Year 2021 by: a. Using 3 moving average b. Using exponential smoothing with alpha = 0.30. The sales manager had predicted, before the business started, that year 1l's sales would be 410 air conditioners. c. Using the relationship between the sales and advertainment spent Which of the above value is the best predicated demand for Year 2021? 2-2 Three trials for the company stock control system were calculated as shown in the table below. The holding cost, shortage cost and ordering costs have been estimated to be $220, $80 and $170. The company has a high competition therefore they need to keep their customer and attract more new customers. Strategy 1 Strategy 2 Strategy 3 Reorder Quantity 200 600 400 Reorder Level 300 400 200 Lead Time 1 Number of days when stock out is occurred 20 12 Number of…
Question 1 ) The monthiy sales Of yamizí Battery company are asfollows:- Month Jales 2000 2100 1500 1400 1300 Calcuiate fore cost sales for June using each of the fo llowing method: - i) Naive Method 1M 3 Month Simple moving averoger Ti) Exponentral smoothing using an a =0:3 cand may forecast of 1600 units.
1. National mixer, Inc. sells can openers. Monthly sales fo a seven-month . period were as follows: Sales Month (000 units) Feb-- -19 March -18 April May June- 15 20 18 July Aug.--- 22 20 a. Forecast September sales volume using each of the following: 1. A five month-moving average 2. The naïve approach 3. A weighted using .60 for August, .30 for July, and .10 for June. b. Which method seems least appropriate? And Why? c. What does use of the term sales rather than demand presume?
B. The owner of a small hardware store has noted a sales pattern that seems to parallel the number of break-inns reported each week in newspaper. The 08 02 05 Sales: 50 22 24 18 35 42 13 Break-inns: 9 04 04 06 08 03 7 Estimate sales when break-inns is 7
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
Indicate how and why each of these factors is important to thesuccessful operation of a supermarket:b. Forecasting
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
1. Solve manually. The following gives the number of pints of type A blood used at Woodlawn Hospital in the past 6 weeks. Pints Used 360 Week August 31 September 7 September 14 September 21 September 28 389 410 381 368 October 5 374 a. Forecast the demand for the week of October 12 using a 3-week moving average. b. Use a 3-week weighted moving average, with weights of 0.1, 0.3 and 0.6, using 0.6 for the most recent week. Forecast demand for the week of October 12. c. Compute the forecast for the week of October 12 using exponential smoothing with a forecast for August 31 of 360 and c=0.2. d. Compute the MAD for the 3-week moving average, 3-week weighted moving average and exponential smoothing models above.
1. Solve manually. a. Income at the law firm Smith and Wesson for the period February to July was as follows: Month Feb Mar Аpr May June July Income $ 70.00 71.30 (in thousand) 68.50 64.30 71.70 72.8 Use trend-adjusted exponential smoothing to forecast the law firm's August income. Assume that the initial forecast for February is $65,000 and the initial trend adjustment is 0. The smoothing constants selected are alpha = 0.1 and beta = 0.2 %3D

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