Using the data below, with a smoothing constant of 0.1 for t…

Using the data below, with a smoothing constant of 0.1 for the base and 0.6 for the trend, compute a trend-adjusted exponential smoothing forecast for period 2. (You are now at the end of period 1.)  Period     At         Ft        Tt   1          640      510       80   2

For the next 2 questions, suppose the following had been com…

For the next 2 questions, suppose the following had been computed for a set of past forecasts. If the “one-number forecast for next period was 1000, what are the lowest and highest demands that we can possibly expect for next period, using a 99.7% confidence level? MSE = 126               MAPE = 21              Tracking Signal = +5                  MAD = 8

Suppose you have the following information from a forecastin…

Suppose you have the following information from a forecasting software package. There are three seasons (terms) each year, and the demand data shown below are for the last 2 academic years (Fall, Spring, and Summer of each year).  You are now sitting at the end of period 9, which is the last term of the third year.  (Note:  The best-fit line equation shown below was made up by me; it may not actually be the true equation if you were to do an analysis of this data.) Demand = 310 + 10 (time)   What would be the forecast for the Spring term of 2024, if you didn’t care about adjusting for any seasonality?

Suppose the following had been computed for a set of past fo…

Suppose the following had been computed for a set of past forecasts. If the “one-number forecast” for next period was 1000, what are the lowest and highest demands that we can possibly expect for next period, using a 99.7% confidence level? MSE = 126               MAPE = 21              Tracking Signal = +5                  MAD = 8 Which of the following would be true about the forecasting method being used?    I.  the method tends to over-forecast   II.  the method misses by 126 units on average  III.  the method has been missing by an average of 8%

Suppose your actual demand and your forecasts for the last 3…

Suppose your actual demand and your forecasts for the last 3 months were as follows.  You are now at the end of period 3.  Period       Demand       Forecast 1                 100                  90 2                 120                100 3                 115                120 Compute the RSFE at the end of period 3.