2. What is the Mean Absolute Deviation (MAD)?3. Use the following set of data to calculate the Mean Absolute Deviation (MAD) for thefollowing set of data.MonthActual (At)Forecast (Ft)Forecast ErrorAbsolute(Deviation)Forecast ErorJanuaryFebruary45454250March3445AprilMay48403845MAD =

Forecasting is the process of predicting the future demand based on previous or historic data and…

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Practical Management Science

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Chapter2: Introduction To Spreadsheet Modeling

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

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The following are monthly actual and forecast demand levels for May through December for units of a product manufactured by the Deborah Bishop Company in Des Moines: Month May June July August September October Actual Demand 108 80 108 115 105 114 125 120 Forecast Demand 100 100 97 101 104 104 108 107 November December For the given forecast, the tracking signal = MADS (round your response to two decimal places). 4
Marianne Kramer, the owner of Handy Man Rentals, rents carpet cleaners to contractors and walk-in customers. She is interested in arriving at a forecast of rentals so that she can order the correct quantities of supplies that go with the cleaners. Data for the last 10 weeks are shown here.Week Rentals Week Rentals1 15 6 202 16 7 243 24 8 274 18 9 185 23 10 16a. Prepare a forecast for weeks 6 through 10 by using a 4-week moving average. What is the forecast for week 11?b. Calculate the mean absolute deviation as of the end of week 10.
a) Apply moving average and exponential smoothing to generate two forecasts of the closing price for the entire data period. Set appropriate values for the forecast parameters (e.g., k and a). b) Plot and compare the actual and predicted data values you calculated in part (b). Provide one chart that displays actual, moving average, and exponential smoothing lines. Hint: Calculate MSE, MAD, or MAPE to compare the different forecasts. Develop your own forecast from scratch. Do NOT use Excel’s Data Analysis or Forecast Sheets.
The owner of Leisure Boutique in a local mall is reviewing their forecasting model for errors. Month Actual Forecasted March 64 63 April 66 67 May 70 71 June 78 75 July 80 79 August 84 83 September 92 87 October 94 91 What is the cumulative forecast error? Group of answer choices a) -16 b) 16 c) 12 d) -12
Consider the following from an estate agent’s business nationally: Month Houses Sold Jan 380 Feb 360 Mar 390 Apr 400 May 390 June 380 July 394 Aug 454 Sep 460 Oct 460 Nov 430 Dec 370 Calculate the three point moving averages (quarters) and seasonal variation for the above data Define moving averages and how they’re useful in forecasting (use Harvard referencing) At races, your horse, White Rum, has a probability of 1/20 of coming 1st, 1/10 of coming 2nd and a probability of ¼ in coming 3rd. First place pays $5,000 to the winner, second place $4,000 and third place $1,350. Hence, is it worth entering the race if it costs $1050? Your company plans to invest in a particular project. There is a 40% chance you will lose $3,000, a 45% chance you will break even, and a 15% chance you will make $5,500.…
i need this to study stop canceling my questions A check-processing center uses exponential smooth- ing to forecast the number of incoming checks each month. The number of checks received in June was 40 million, while the fore- cast was 42 million. A smoothing constant of .2 is used. a) What is the forecast for July?b) If the center received 45 million checks in July, what would be the forecast for August?c) Why might this be an inappropriate forecasting method for the situation
Given the following data of actual sales and forecast for the five months: Month 1, Month 2, Month 3, Month 4, Month 5, and Month 6: Month 1 2 3 4 5 6 Actual Sales 50 40 45 55 65 50 Forecast 55 50 (b) Calculate the Mean Square Error (MSE). (a) Calculate the Mean Absolute Percent Error (MAPE). 40 50° 65 40 (c) Calculate the Mean Absolute Deviation (MAD).
The following data are for calculator sales in units at an electronics store over the past nine weeks: Week Sales Week Sales 1 45 53 2 50 7 59 3 44 8. 59 4 51 9 64 5 57 Use trend projection with regression to forecast sales for weeks 10 - 13. What are the error measures (CFE, MSE, o, MAD, and MAPE) for this forecasting procedure? How about ? Obtain the trend projection with regression forecast for weeks 10 – 13. (Enter your responses rounded to two decimal places.) Period Forecast, F, 10 64.81 11 67.06 12 69.31 13 71.56 Obtain the error measures. (Enter your responses rounded to two decimal places.) CFE MSE MAD МАРЕ
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4) A small manufacturing firm has recorded a time series of the cost per unit for the firm's leading product over the past eight years. Year Cost/Unit($) 1 2 3 4 5 6 7 8 20 24.5 28.2 27.5 26.6 30 31 36 a) If you are not given a base value or trend, what would be the forecast for the year 10 made at the end of year 8 (a=0.2, ß=0.4). b) Forecast for the year 9 using 1) 5-month weighted average using 0.1,0.1,0.1,0.2,0.3, with the heaviest weight applied to the recent month 2) Exponential smoothing using a =0.2 and forecast of 21 for year 5 3) If a value was not provided in the question above, what value of a would you choose?
Month Demand Sept. 78 Oct. 80 Nov. 77 Dec. 85 Jan. Based on the time series data presented above, do the forecasts using 2-month moving average (2-MA) and single exponential smoothing (SES) with a = 0.4, and answer the following questions: %3D (i) What is the mean absolute deviation (MAD) for 2-MA? (ii) What is the mean absolute deviation (MAD) for SES a = 0.4 ? (iii) Based on what you got, which method is more accurate?
Below is a table containing data on product demand for the most recent three months along with the forecasts that had been made for those three previous months. Calculate the MAE (or MAD). Month Demand Forecast 1 308 310 2 388 390 3 344 342

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