155Two independent methods of forecasting based onjudgment and experience have been prepared eachmonth for the past 10 months. The forecasts and actualsales are as follows:1Month Sales Forecast 1835845212345678910Forecast850820785840815840785800Forecast835830840790815785770835a. Compute the MSE and MAD for each forecast. (Roundyour answers to 2 decimal places.)MSEMAPE F1MAPE F2805785Answer is complete but not entirely correct.MAD2,942.50 xForecast 27658301,125.60 x8158308008067758108158054.2153 X %3.4380 %22.50✔Return to question28.40✔b. Compute MAPE for each forecast. (Round yourintermediate calculations to 5 decimal places and finalanswers to 4 decimal places.)> Answer is complete but not entirely correct.c. Prepare a naive forecast for periods 2 through 11 usingthe given sales data. Compute each of the following; (1)MSE, (2) MAD, (3) tracking signal at month 10, and (4) 2scontrol limits. (Negative values should be indicated by aminus sign. Round your answers to 2 decimal places.)

Here, for each month, I am given actual sales data, forecast 1 data, and forecast 2 data, Now, I…

Answered: a. Compute the MSE and MAD for each…

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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Respond to each of the items using the following time series data. Period Demand 144 2 172 3 157 4 160 144 181 7 160 8 176 9. 149 10 183 11 182 12 149 13 153 14 164 15 153 16 104 Click here for the Excel Data File b. Compute all possible forecasts using a five-period moving average. (Round your answers to 1 decimal place.) Absolute Period Demand 5-period SMA Errors 1 144 172 3 157 4. 160 5 144 181 7 160 8 176 9 149 10 183 11 182 12 149 13 153 14 164 LO
a. What is the mean square error for time periods 2 through 4 using the average forecasting method? b. What is the mean absolute error for time periods 2 through 4 using the average forecasting method? c. What is the mean absolute percentage error for time period 2 through 4 using the average forecasting method? Round all answers to two decimal places. Time Period 1 2 3 4 Mean absolute error (MAE) Mean squared error (MSE) Mean absolute percentage error (MAPE) Electric Bill 510 315 420 480 Average Forecast Forecast Error
Assume that your stock of sales merchandise is maintained based on the forecast demand. If the distributor's sales personnel call on the first day of each month, compute your forecast sales by each of the three methods requested here. June July August ACTUAL 144 184 210 a. Using a simple three-month moving average, what is the forecast for September? Note: Round your answer to 2 decimal places. Forecast for September b. Using a weighted moving average, what is the forecast for September with weights of 0.30, 0.40, and 0.30 for June, July, and August, respectively? Note: Do not round intermediate calculations. Round your answer to 2 decimal places. Forecast for September
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
January February March April May June a. Calculate forecasts for the remaining five months using simple exponential smoothing with a = 0.4. February March April May June ACTUAL FORECAST 100 85 96 103 82 66 90 MAD Forecasts 91 93 97 91 81 b. Calculate the MAD for all the forecasts, including January's. (Round your answer to 1 decimal place.)
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) 16
The Toro Cutlery Company has collected monthly sales information below: MONTH January February March April The company is examining two forecasting methods, moving average and exponential smoothing for forecasting sales. a. What will the forecast be for January the following year using a three-, four-, and five-month moving averages? Do not round intermediate calculations. Round your answers to the nearest whole number. Forecast (January, 3-month MA): 87667 Forecast (January, 4-month MA): 72500 Forecast (January, 5-month MA): 69600 b. What will the forecast be for January the following year using exponential smoothing with a = 0.6? Assume the forecast for February this year is 25,000. Do not round intermediate calculations. Round your answer to the nearest whole number. SALES 25,000 18,000 43,000 110,000 MONTH May June July August SALES MONTH 84,000 September 28,000 October 97,000 November 58,000 December SALES 27,000 105,000 82,000 76,000
Given the following sales data: week 1: 203 week 2: 185 week 3: 164 week 4: 151 week 5: 115 Forecast sales for week 6 using Holt's model with: alpha = 0.3 beta = 0.4 Use L(2) = A(2) and T(2) = A(2) - A(1) to initialize the model. %3D Your Answer: Answer
a. Use a 3-month moving average to estimate the month-in-advance forecast of demand for months 4–12 and generate a forecast for the first month of next year. Calculate the average forecast error and mean absolute error. b. Use a 3-month weighted moving average with weights of 0.6, 0.3, 0.1 (most recent to least recent, respectively) to calculate month-in-advance forecasts for months 4–12 and forecast for the first month of next year. Calculate the average forecast error and mean absolute error. c. Compare the average forecast error and MAD for the forecasting methods in parts a and b. Based on these error calculations, which of the two forecast methods would you recommend? Why?
a. Using POM for Windows' least squares-linear regression module, develop a relationship to forecast production ratings from test scores. (Round your responses to three decis and include a minus sign if necessary.) Y= - 23 + .945 x where Y = Production rating and X = Test score. b. If a worker's test score was 54, what would be your forecast of the worker's production rating? 51. (Enter your response as an integer.) c. Comment on the strength of the relationship between the test scores and production ratings. The coefficient of correlation for the least-squares regression model is and the coefficient of determination is (Enter your responses rounded to three decimal places.) More info Test Score Production Rating Production Test Worker Worker Rating Score A 55 43 K 58 57 B 38 43 75 75 93 87 67 48 D 86 77 31 26 E 88 82 62 49 F 66 68 24 25 G 55 47 Q 78 84 Clear all Check 50 46 34 32 41 41 51 58 J 69 74 T 39 30 Print Done LLMN OPoRS
Part C Exponential Exponential Gasoline Demand Gasoline Month smoothed forecast smoothed forecast Exponential smoothed forecast (a = 0.25) Demand (a = 0.25) (a = 0.45) Exponential smoothed forecast (a = 0.45) Mar 900 920 920 1200 Apr May 755 915.00 911.00 1100 1000 650 875.00 840.80 g20 915.00 846 80 755 818.75 754.94 904.76 835.12 Jun 550 818.75 754.94 800 320 751.56 66272 645.74 746.83 Jul 625 751.56 662.72 650 600 550 Aug Sep 730 719.92 645.74 820 722.44 683.66 400 D Oct 1100 746.83 745.01 200 1 Nov 835.12 904.76 Mar Apr May Jun Jul Aug Sep Oct Nov 1. Make a comparative analysis out of your answers in the plotted data. (3-5 5 sentences)
Forecast based on averages. Given the following data: Period Number of Complaints 1 70 2 75 3 65 4 68 5 74 Prepare a forecast for period 6 using each of these approaches: a. A weighted average using weights of .50 (most recent), .30, .20 b. Exponential smoothing with a smoothing constant of .40

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