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.)Answer is complete but not entirely correct.MSEMADTracking signalControl limits0±I+28.33 X1,221.88 x-1.2569.91 Problem 3-22 (Algo)Two independent methods of forecasting based onjudgment and experience have been prepared eachmonth for the past 10 months. The forecasts and actualsales are as follows:Month Sales835845850820785840815840785800123456780910Forecast 1835830840790815785770835805785Forecast 2765830815830800806775810815805

Forecast helps in knowing future events or trends, mainly based on the available data, analysis, and…

Answered: c. Prepare a naive forecast for periods…

Practical Management Science

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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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(4) Exponential smoothing with a smoothing constant equal to 0.15, assuming a March forecast of 15(000). (Round your intermediate forecast values and final answer to 2 decimal places.) Forecast thousands (5) A linear trend equation. (Round your intermediate calculations and final answer to 2 decimal places.) Yt thousands
6. Consider the following data table. (12 Points) a) Forecast demand using exponential smoothing with an apha of 0.25, and an initial forecast of 128.0 for period 1. b) Calculate the MAD and MSE. Period Real demand 130 138 129 140 3 4 5 133
Use simple exponential smoothing with a=0.6 to forecast chargers sales for February through May. Assume that the forecast for January was 24 chargers. *** Month January Charger Sales 42 February 33 March 28 April 59 May ? a) What will be the forecast for May? b) Calculate the MSE.
Asvnch Problem - Statistical Forecasting Data Set – Eunice BC Fashion Monthly Sales, in million units. Year Total Sales Year Total Sales 2010 38 2016 43 2011 41 2017 40 2012 40 2018 45 2013 45 2019 47 2014 50 2020 42 2015 42 2021 48 Questions: a. Find the naïve forecast. b. Use the 3 years moving average forecast. c. Have a 5 years weighted moving average. d. Develop forecast using exponential smoothing with a = 0.2. e. Determine the trend line equation and present the forecast. f. Find the best forecast for year 2022. Note: Use the first 5 years as the training samples and the last 5 years as the forecasting samples. Solve it in Excel Sheet/Sheet with Equations as possible.
Given the following original forecast and actual data: Month Actual Forecast Jan 600 Feb 475 Mar 550 Apr 575 May 643 Jun 662 Jul ??? ??? Using a 2 month weighted moving average with weights of 75% for the previous month and 25% for two months back, what is the forecast for July. Round your answer to 1 decimal place. 400 -- —— ——
Marianne Schwartz, 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. Part 2 Week 1 2 3 4 5 6 7 8 9 10 Rentals 23 22 25 23 22 11 21 34 19 13 Part 3 a. Prepare a forecast for weeks 6 through 10 by using a 4-week moving average LOADING... . (Enter your responses rounded to two decimal places.) Week Forecast 6 enter your response here Part 4 7 enter your response here Part 5 8 enter your response here Part 6 9 enter your response here Part 7 10 enter your response here Part 8 What is the…
Given the following historical data, what is the simple three-period moving average forecast for period 6? Period 1 2 3 4 5 67.67 68.2 67.3 68.4 Value 73 66 64 73 66
Given the following original forecast and actual data: Month Actual Forecast Jan 600 Feb 475 Mar 550 Apr 575 May 643 Jun 662 Jul ??? ??? Using a 2 month weighted moving average with weights of 75% for the previous month and 25% for two months back, what is the forecast for July. Round your answer to 1 decimal place. 400 -- —— ——
41) A medium-term forecast is considered to cover what length of time? A) 2-4 weeks B) 1 month to 1 year C) 2-4 years D) 5-10 years E) 20 years 42) When is the exponential smoothing model equivalent to the naÃ¯ve forecasting model? A) ? = 0 B) ? = 0.5 C) ? = 1 D) during the first period in which it is used E) never 43) Enrollment in a particular class for the last four semesters has been 120, 126, 110, and 130. Suppose a one-semester moving average was used to forecast enrollment (this is sometimes referred to as a naÃ¯ve forecast). Thus, the forecast for the second semester would be 120, for the third semester it would be 126, and for the last semester it would be 110. What would the MSE be for this situation? A) 196.00 B) 230.67 C) 100.00 D) 42.00 E) None of the above 44) Which of the following methods tells whether the forecast tends to be too high or too low? A) MAD B) MSE C) MAPE D) decomposition E) bias 45) Assume that you have tried three different…
Centerville Bikes and Stuff (CBS) sells motorcycles and accessories. The number of helmets sold by CBS per week for the past six weeks follows. Week 1 2 Value 17 14 15 3 (b) mean squared error MSE = % 4 Using the naive method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy. (a) mean absolute error MAE = 5 6 (d) What is the forecast for week 7? 12 16 15 (c) mean absolute percentage error (Round your answer to two decimal places.) MAPE =
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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?

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c. Prepare a naive forecast for periods 2 through 11 using the given sales data. Compute each of the following; (1) MSE, (2) MAD, (3) tracking signal at month 10, and (4) 2s