Week 1 2 4 Forecast Method 1 0.90 1.05 0.97 1.22 Actual Demand 0.72 1.05 1.00 0.97 Week 1 2 3 4 Forecast Method 2 0.82 1.19 0.90 1.17 Actual Demand 0.72 1.05 1.00 0.97 0 The MAD for Method 1 = thousand gallons (round your response to three decimal places). The mean squared error (MSE) for Method 1 = thousand gallons (round your response to three decimal places). The MAD for Method 2 = thousand gallons (round your response to three decimal places). The mean squared error (MSE) for Method 2 = thousand gallons (round your response to three decimal places).

Week 1 2 4 Forecast Method 1 0.90 1.05 0.97 1.22 Actual Demand 0.72 1.05 1.00 0.97 Week 1 2 3 4 Forecast Method 2 0.82 1.19 0.90 1.17 Actual Demand 0.72 1.05 1.00 0.97 0 The MAD for Method 1 = thousand gallons (round your response to three decimal places). The mean squared error (MSE) for Method 1 = thousand gallons (round your response to three decimal places). The MAD for Method 2 = thousand gallons (round your response to three decimal places). The mean squared error (MSE) for Method 2 = thousand gallons (round your response to three decimal places).

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...

See similar textbooks

Similar questions

Exercise Torecast CIT ▷ Complete the table Month 1 2 3 4 5 6 Forecast demand 700 760 780 790 850 950 Actual demand 660 840 750 835 910 890 ▷ What is MAD? MAPE? TS? Deviation RSFE (Cumulative sum of forecast errors) MAD (Mean absolute deviation) APE (absolute % error) +
Can you assit me with this problem 8 by showing me the process step by step. I prefer it not be in the form of an excel sheet because it is hard to follow along. Thank you kindly
Calculate the Mean Squared Error for the following data: Actual 90 87 96 102 Forecast 89.3 89.2 93.3 90.7 (Keep two decimal places in your answer)
14.5. For the data in Exercise 14.4, use an a of 0.1 to make a forecast for July F Ft-1 + 0.1(At-1-Ft-1) Months January 15 February 18 March 22 23 27 26 April May June Demand Smoothing unit (At) (St) July 15 15.3 15.97 16.67 17.7 18.53 Forecast for July= 18.53 Forecast (Ft) 15 15.3 15.97 16.67 17.7 18.53
The following table gives the number of pints of type A blood used at Damascus Hospital in the past 6 weeks: Week of Pints Used August 31 360 September 7 370 September 14 412 September 21 383 September 28 371 October 5 371 a) The forecasted demand for the week of October 12 using a 3-week moving average= {__] Pints (round your response to two decimal places).
An electrical contractor's records during the last five weeks indicate the number of job requests: Week: Requests: 1 2 3 5 25 27 25 26 27 Click here for the Excel Data File Predict the number of requests for week 6 using each of these methods: a. Naive. Number of requests b. A four-perlod moving average. (Round your answer to 2 decimal places.) Number of requests
Data collected on the yearly registrations for a Six Sigma seminar at the Quality College are shown in the following table: Year -1 2 Registrations (000) 5.0 5.0 Year Forecast 4 4.3 This exercise contains only parts a and b. a) Using a 3-year moving average, the forecasted registrations (in thousands) for years 4 through 12 are (round your responses to one decimal place): 5 4.6 4 3 3.0 5 6 6.6 7 8 4 5 6 9 10 6.0 11.0 9.0 7.0 9.0 13.0 16.0 6 7 8.7 8 9 7 9 8.3 b) Using a 3-year weighted moving average in which the registrations in the most recent year are given a weight of 2, and registrations in the other 2 years are each given a weight of 1, the forecasted registrations (in thousands) for years 4 through 12 are (round your responses to one decimal place): Year Forecast 8 10 9.6 9 11 12.6 10 12 15.3 11 11 17.0 12
Plz 100% correct solution needed.
In the past Peter Kelles tire dealership in Baton Rouge sold an average of 1,100 radial each year. In the past 2 years, 220 and 240 respectively were sold in fall, 360 and 320 in winter and 140 and 160 in spring and 300 and 460 in summer. with a major expansion planned, Kelle projects sales next year to increase 1300 radials. Based on next years projected sales the demand for each season is going to be (enter your response as whole numbers) season demand fall [___]
Three years ago CMSV admissions office began using exponential smoothing with a smoothing constant of 0.25 to forecast the number of applications for admissions each year. Based on the previous experience, this process was begun with an initial estimate of 5000 applications. The actual number of applications turned out to be 4600 in the first year and grew to 5300 in the second year and 6000 last year. Determine the forecasts that were made for each of the past three years. Calculate MSE and MAD for these three years and determine the forecast for the next year.
Calculate the Mean Squared Error for the following data: Actual 90 85 96 99 Forecast 91.3 87.6 93.2 98.6 (Keep two decimal places in your answer)
An auditor used regression analysis to evaluate the relationship between utility costs andmachine hours. The following information was developed using a computer softwareprogram: Intercept 2,050 Standard error of estimate 200Regression 0.825 Number of observations 36Correlation coefficient 0.800 How much is the utility cost if the company’s 10 machines will use 2,400 hours next month?a. ₱3,830b. ₱3,970c. ₱4,030d. ₱4,050