Omgt

OMGT 3233 Assignment 3

1.

A. For the three-month moving average forecast, we computed 1.89 as the 2-Month moving average MAE. This also happened to be the ultimate choice when choosing which forecast to use. This forecast had the smallest margin of error.

B. For the five-month moving average forecast, we computed 2.43 as the 5-month moving average MAE. We chose not to use this forecast when calculating the forecast for January because it has a larger margin of error.

C. Below, we have the scatter plot for the comparison of the different forecasting approaches. You can see through the chart the margin error for each forecast.

D. Comparing the three-month moving average and the five-month moving average, we chose the three-month as the most accurate forecast. Using this forecast, we developed a forecast for January and came up with 13.33 as the amount of sales for that month.

2

D. When we compared the three approaches using the MSE, we identified the most accurate approach to be the 3 semester MA. Using this approach, we forecasted semester 9 will have 420 students enrolled.

3.

A. B.

C. When we predicted the equation for calls presented as a function of forecasted calls, we came up with Y= 99.90+0.86x.

D. We calculated 107 as the MAE for the linear regression model. From this, we can conclude that on average, the actual calls and calls forecasted are going to be off by this amount.

E. Using our regression model, a forecast of 750 calls would mean that there would be 744 actual calls that day.

4.

We started the problem by performing a multiple regression analysis which is located under the data analysis tab in excel. We clicked on the regression option and enter the data into the appropriate areas. For the Input Y Range we entered: $C$2:$C$37. For the Input X Range we entered $D$2:$H$37. After running the analysis we pasted our results in J11. We then had to find the coefficient of determination with equals R squared...