A.) Compute the 3-period simple moving average forecasts. Compute the MAD and MSE for the 4-period simple moving average. B.) Compute the 4-period weighted moving average forecasts using the weights=0.25, 0.1, 0.44, and 0.3. Compute the MAD and MSE for the 3-period weighted moving average. C.) Compute the exponential smoothing forecasts using alpha=0.35. Compute the MAD and MSE for the exponential smoothing forecasts.

Please help with the correct answers in details:   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 3 4 5 6 Value 19 12 17 10 18 15 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 =  (b) mean squared error MSE =  (c) mean absolute percentage error (Round your answer to two decimal places.) MAPE =  % (d) What is the forecast for week 7?

Please answer it ASAP. With only short explanation. Please answer fast i will really upvote.

Demand for oil changes at Garcia's Garage has been as follows: Number of Oil Changes January 44 February 49 March 66 IT April 59 May 53 June 58 59 63 Month July August a. Use simple linear regression analysis to develop a forecasting model for monthly demand. In this application, the dependent variable, Y, is monthly demand and the independent variable, X, is the month. For Janu The forecasting model is given by the equation Y=+x. (Enter your responses rounded to two decimal places) J Show Transcribed Text >. Use the model to forecast demand for September, October, and November. Here, X=9, 10, and 11, respectively. (Enter your responses rounded to two decimal places.) Forecast for the number of Oil Changes Show Transcribed Text Month September October November can you do all the parts please corrrect

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Tom Simpson, Director of the Chamber of Commerce for Exeter township is investigating the past ten years of tourist visits to the area.  The following data has been gathered on number of tourists who signed into the local information center. Year Number of tourists 1 700 2 248 3 633 4 458 5 1410 6 1588 7 1629 8 1301 9 1455 10 1989 What is the forecasts for Year 11 using the simple moving method? (show in calculations in excel file)

Demand for oil changes at Garcia's Garage has been as follows: Month January February March April May June July August Number of Oil Changes 38 55 56 60 58 01 70 52 a. Use simple linear regression analysis to develop a forecasting model for monthly demand. In this application, the dependent variable, Y, is monthly demand and the independent variable, X, is the month. For January, let X=1; for February, let X 2; and so on. The forecasting model is given by the equation Y=X (Enter your responses rounded to two decimal places)

The following data are for calculator sales in units at an electronics store over the past nine weeks: Week Sales Week Sales 45 6 53 50 7 59 44 8 59 51 64 57 Use trend projection with regression to forecast sales for weeks 10 - 13. What are the error measures (CFE, MSE, G. 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 MAPE 6.72 2.75 2.1 4.1 % Find the coefficient of determination (). The coefficient of determination ? = (Enter your response rounded to two decimal places.)

Use regression or simple exponential smoothing with the following data. For exponential smoothing, assume the forecast for year 1 was the same as the actual and use an alpha of 0.7. (use excel to show formauls used)  Year Sales 1 290 2 340 3 400 4 410 5 400   1. What is the tracking signal for the forecast?

Can you please solve all parts of the question manually. Thank you!