hello. ive one document and two questions. ive searched for answers on coursehero for these questions but numbers and questions are different . you can copy paste excel solutions to the word file. it needs to be done step by step and needs to be clear. thank you

Forecasting accuracy edit] [ The forecast error is the difference between the actual value and the forecast value for the corresponding period. where E is the forecast error at period t, Y is the actual value at period t, and F is the forecast for period t.Measures of aggregate error: Mean absolute error (MAE) Mean Absolute Percentage Error (MAPE) Mean Absolute Deviation (MAD) Percent Mean Absolute Deviation (PMAD) Mean squared error (MSE) or Mean squared prediction error (MSPE) Root Mean squared error (RMSE) Forecast skill (SS) Average of Errors (E) 1 Question 1 The U.S. Census Bureau publishes data on factory orders for all manufacturing, durable goods, and nondurable goods industries. Shown here are factory orders in the United States from 1987 through 1999 ($ billion). (a) Use these data to develop forecasts for the years 1992 through 2000 using a 4-year moving average. (b) Use these data to develop forecasts for the years 1992 through 2000 using a 4-year weighted moving average. Weight the most recent year by 4, the previous year by 3, the year before that by 2, and the year before that by 1. (c) Which method is more suitable for forecasting factory orders? Hint: Compare the two methods based on Mean Absolute Deviation (MAD)? Year 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 Factory Orders ($ billion) 2,512.7 2,739.2 2,874.9 2,934.1 2,865.7 2,978.5 3,092.4 3,356.8 3,607.6 3,749.3 3,952.0 3,949.0 4,137.0 2 Question 2 The following table lists the worldwide shipments of personal computers (in thousands) according to Dataquest. Year Shipments (in thousands ) 1990 23,738 1991 26,966 1992 32,411 1993 38,851 1994 47,894 1995 60,171 1996 71,065 1997 82,400 1998 97,321 (a) Use exponential smoothing to determine the forecast of shipments for the year 1999. Use the actual shipments for 1990 as the starting forecast for 1991. Use a smoothing constant of 0.4. (b) Plot the data, fit a trend line, display equation and on the chart and discuss the strength of prediction of the regression model. (Hint: Use 1990 = 1, 1991 = 2, and so on to get more accurate equation). (c) Use the regression model to predict the shipments for the years 1992 through 1999. (d) Which forecasting method would you prefer to use and why (Please see residual plot for hint)? (Note: Compute MAPE for the two forecasting methods to compare the accuracy for the period 1992-1998). 3