Daily high temperatures in st. Louis for the last week were as follows: 33,33,38,36,43,23,28(yesterday).Calculate the mean absolute deviation based on a 3 day moving average?In my text book it say that you need the actual forecast however, the problem never gives me the real temp thus creating a problem to calculate mean absolute deviation? any help would be greatly appreciated

12.7 The Intrepid mutual fund of growth stocks has had the following average monthly price for the past 10 months. Month 1 2 3 4 5 6 7 8 9 10 Fund Price 62.7 63.9 68.0 66.4 67.2 65.8 68.2 69.3 67.2 70.1 Compute the exponentially smoothed forecast with a = 0.40, the adjusted exponentially smoothed forecast with a = 0.40 and ß = 0.30, and the linear trend line forecast. Compare the accuracy of the three forecasts using cumulative error and MAD, and indicate which forecast appears to be most accurate.

Given an actual demand this period of 90, a forecast for this period of 58, and an alpha of 0.2, what would the forecast for the next period be using exponential smoothing?

One forecasting model was used to forecast demand for a product. The forecasts and the demand are shown in the table below. Use two decimals in your answer. Actual Forecast 1 40 41 2 35 38 3 38 35 4 33 30 The Mean Absolute Deviation (MAD) is O 0.5 2.5 O 1.48 7.01

The Carbondale Hospital is considering the purchase of a new ambulance. The decision will rest partly on the anticipated mileage to be driven next year. The miles driven during the past 5 years are as follows Year Mileage 1 3,100 2 4,000 3 3,450 4 3,850 5 3,750 a) Using a 2-year moving average, the forecast for year 6 = 3800 miles (round your response to the nearest whole number). b) If a 2-year moving average is used to make the forecast, the MAD based on this = 108.3 miles (round your response to one decimal place). (Hint. You will have only 3 years of matched data.) c) The forecast for year 6 using a weighted 2-year moving average with weights of 0.40 and 0.60 (the weight of 0.60 is for the most recent period) = miles (round your response to the nearest whole number)

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.

Sales of Bluetooth Headphones at the Abdulla Electronics Enterprises in Model Town, India, over the past 4 months have been 100, 110, 120, and 130 units (with 130 being the most recent sales). Develop a moving-average forecast for next month, using following techniques:    a) 3-month moving average. b) 4-month moving average. c) Weighted 4-month moving average with the most recent month weighted 4, the preceding month 3, then 2, and the oldest month weighted 1. d) If next month’s sales turn out to be 140 units, forecast the following month’s sales (months) using a 4-month moving average.

I would I do a problem like this? A time-series trend equation is 20.6 + 15.7x. What is your forecast for period 13?

Give an example of forecasting a pet store

The number of cans of soft drinks sold in a machine each week is recorded below. Develop forecasts for the period indicated and error calculations. 155, 145, 155, 162, 180, 165, 172, 149, 170, 172 Exponential smoothing.  Use Excel Solver to determine the optimum alpha value to minimize MSE and answer: What is the Mean Absolute Percentage Error (MAPE)?