MGMT 3100-Use Exponential smoothing with alpha
1. QUESTION 1Use Exponential smoothing with alpha=0.2 to forecast the sales for April using thedata given below (Use two decimal points): JanFebMar 1. 1. 576597 QUESTION 2Using Sales of the past eight quarters (from t=1 to t=8), the following trend modelwas generated using a simple linear regression (Sales is the dependent (y) variable andTime is the independent variable).Sales = 45 + 8 * t (Intercept is 45 and Slope is 8).Calculate the forecast for time period 10. (Keep two decimals) QUESTION 3Use the three period Moving Average method to forecast the sales for June using thedata given below (Use two decimal points):JanFebMarAprMay 7156988889 2.3. 1. QUESTION 4Which of the following is TRUE (check all the correct choices, wrong answers will incurnegative marking)To find MSE, you need to find the square of the difference between the actual value andthe forecast and then sum all these differences squared.To find MAPE, you need to find the absolute difference between the actual value and theforecast, then divide this absolute difference by the forecast value. Then take theaverage of all these absolute percentage errors.To find MAD, you need to find the difference between the actual value and the forecastand then take the average of all these differencesTo find MAPE, you need to find the absolute difference between the actual value and theforecast, then divide this absolute difference by the actual value. Then take the average of all these absolute percentage errors.In the multiplicative time series model, the trend component is first found by usingregression. Then the seasonal component (index) is identified using the data. These twocomponents are then multiplied to get the final forecast.To find MAD, you need to find the absolute difference between the actual value and theforecast and then take the average of all these absolute differencesIn the multiplicative time series model, the trend component is first found by using theoverall average. Then the seasonal component (index) is identified using the data.These two components are then multiplied to get the final forecast.To find MSE, you need to find the square of the difference between the actual value andthe forecast and then take the average of all these differences squared.1. QUESTION 5In the context of forecasting, an indexIs independent of X (that is, time), hence thename Index.Is a detailed list of different variables.Is a combination of indicators withassociated weights.A shortcut that points to where the data is.