a. Construct a time series plot. What type of pattern exists in the data? b. Compare a two-week moving average forecast with an exponential smoothing forecast for a = 0.4, which provides the better forecasts using MSE as the measure of model accuracy? c. Create a linear trend projection model to make a sales forecast and evaluate the accuracy of the sales forecast. d. Based on the results, which is the best forecasting model to be used to forecast the 13th week sales?

It wouldnt let me take a screenshot of the table so I had to copy and paste it in here. My question is: How do you Calculate a moving average forecast using the last 2 and 4 dates of stay. What is the prediction for 7/1/2021 for each technique? Discussion Question 1 - 200 room hotel                                   Forecasts   MA 2 Errors MA 4 Errors ES (0.8) Errors ES (0.5) Errors   Date Day of Week Rooms Sold MA 2 MA 4 ES (0.8) ES (0.5)   AE APE AE APE AE APE AE APE   6/1/2021 Tuesday 123                             6/2/2021 Wednesday 109                             6/3/2021 Thursday 140                             6/4/2021 Friday 199                             6/5/2021 Saturday 179                             6/6/2021 Sunday 140                             6/7/2021 Monday 117                             6/8/2021 Tuesday 132                             6/9/2021 Wednesday 108                             6/10/2021 Thursday 151…

discuss the strategic importance of forecasting for Disney and demonstrate how Disney World systematically uses the first seven steps in the forecasting process to initiate, design and implement forecasting systems

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.)

Which​ time-series forecasting method works best if the company assumes that product demand will decrease over​ time?     A. Weighted moving average   B. Linear trend   C. Moving average   D. Exponential smoothing

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

Please answer all questions!

Here are the actual tabulated demands for an item for a nine-month period (January through September). Your supervisor wants to test two forecasting methods to see which method was better over this period.   MONTH ACTUAL January 120 February 145 March 146 April 171 May 154 June 182 July 138 August 135 September 146     a. Forecast April through September using a three-month moving average. b. Use simple exponential smoothing with an alpha of  0.20 to estimate April through September, using the average of January through March as the initial forecast for April.  c-1. Calculate MAD for Three-month moving average and Exponential smoothing. c-2. Use MAD to decide which method produced the better forecast over the six-month period.

I just need the part D!

If month one has 240,000 demands, month two 250,080 demands, month three 325,00 demands, month four 370,000 demands, month five 420,000 demands and month six 509,00 demands. Use a forecast for the first month of 240,000, an initial trend forecast of 50,000, and smoothing parameters of 0.35 for both demand smoothing and trend smoothing. Compute the forecasts and trends using double exponential smoothing