Months 1 2 3 14 885 Using exponential smoothing, with a smoothing constant of 0.14, forecast the number of customers for Month 5. (round to nearest whole number) O 779 920 830 Number of Customers O 1005 750 1920 810 1144

Table 6 shows the year and the number ofpeople unemployed in a particular city for several years. Determine whether the trend appears linear. If so, and assuming the trend continues, in what year will the number of unemployed reach 5 people?

The US. import of wine (in hectoliters) for several years is given in Table 5. Determine whether the trend appearslinear. Ifso, and assuming the trend continues, in what year will imports exceed 12,000 hectoliters?

Using Excel, run descriptive analysis for the first 12 months, the next 12 months, etc., on the dataset. Determine the 12 period moving average forecasts and the simple exponential smoothing forecasts (α = 0.05) based on the data. The mathematical formulas for these forecasting techniques are as follows. N period Moving Average Forecast (for next period) = (Sum of Actuals for N number of previous periods) / N. Note: For this assignment, assume N=12. Simple Exponential Smoothing Forecast (for next period) = Previous Period Forecast + (α * (Previous Period Actual - Previous Period Forecast)). Note: For this assignment, assume α = 0.05. For the Period 1, assume that the Forecast is the same as the Actual.value. Mean Absolute %Error = Average of: ((|Actual - Forecast|) / Actual )) for all periods where Actuals and Forecasts exist. Create a line chart for each forecast and ensure that each line chart also contains the historical dataset.  Compute the mean absolute percentage error for each…