Consider the following set of time series sales data for a growing company over the past 8 months: Month Sales 15 2 13 3 18 4 22 20 6. 23 7 22 8. 21

The following are monthly actual and forecast demand levels for May through December for units of a product manufactured by the Deborah Bishop Company in Des Moines: Month May June July August September October Actual Demand 105 82 110 112 108 106 130 120 Forecast Demand 100 108 97 98 108 102 105 107 November December For the given forecast, the tracking signal = MADS (round your response to two decimal places).

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)

If the weights for a moving average forecast with a span of 4 are: 0.4,0.2,0.3,0.1     Problem: Under prediction     Problem:  Over prediction     No problem

Pravinbhai

Professor Very Busy needs to allocate time next week to include time for office hours. He needs to forecast the number of students who will seek appointments. He has gathered the following data: Week 6 weeks ago 5 weeks ago 4 weeks ago 3 weeks ago 2 weeks ago Last week # Students 83 110 95 80 65 50 What is this week's forecast using trend-adjusted (double) smoothing with alpha = .5 and beta = .1, if the forecast for last week was 65, the forecast for two weeks ago was 75, and the trend estimate for last week's forecast was -5? 49.3 78.7 51.3 50.6 65.4

Please answer all questions!

Since the beginning of the year, the purchase manager at a department store has been recording sales data to be used to compute 4-period moving averages to forecast sales for an upcoming month. Sales data for the months of January through September are reported in the table below. Month January February March April May June July August September Sales 21 20 39 22 29 14 42 28 27 Computed forecast values are not rounded. Compute the four-period moving average forecast for October. value as a whole number by rounding. Specify the Compute the mean absolute deviation (MAD) for the four-period moving average forecasts. Specify the MAD as a whole number by rounding. Compute the mean squared error (MSE) for the four-period moving average forecasts. Specify the MSE as a whole number by rounding. Compute the mean absolute percentage error (MAPE) for the four-period moving average forecasts. Specify the MAPE as a whole number by rounding. CHECK ANSWER

Hi, I need help with solving for the following values (boxed). Thank you.

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