Crossland Construction’s design/build department allows their clients (owners) to select the design and construction team based on their combined experience and track-record. Design/build firms typically have a cash flow problem since they tend to be paid in lump sums when projects are completed or hit milestones. However, their expenses, such as payroll, must be paid regularly. So, such firms need bank lines of credit to finance their initial costs, but in the past year, lines of credit were difficult to negotiate. The data file Crossland Construction contains month-end cash balances for the past 16 months. a) Plot the data as a time-series graph. Fit a linear line to the data. Discuss what the graph implies concerning the relationship between cash balance and the time variable, month. b) Fit a linear trend model to the data. Compute the coefficient of determination. Discuss the appropriateness of the linear trend model. What are the strengths and weaknesses of the model? c) Referring to part b), compute the MAD and MSE for the 16 data points. d) Plot the data as a time-series graph. Fit a polynomial line to the data. Discuss what the graph implies concerning the relationship between cash balance and the time variable, month. e) Use the t2 transformation approach and recompute the linear model using the transformed time variable. Discuss whether this model appears to provide a better fit than did the model without the transformation. Compare the coefficients of determination for the two models. Which model seems to be superior, using the coefficient of determination as the criterion? f) Referring to part e), compute the MAD and MSE for the 16 data values. Discuss how these compare to those that were computed in part c), prior to transformation. Do the measures of fit (R2, MSE, MAD) agree on the best model to use for forecasting purposes? g) Use the linear trend model (without transformation) for the first 15 months and provide a cash balance forecast for month 16. Then use the transformation model for the first 15 months and provide a cash balance forecast for month 16. Now, compare the accuracy of the forecasts with and without the transformation. Which of the two forecast models would you prefer? Explain your answer.
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Month | Cash Balance |
1 | 75 |
2 | 70 |
3 | 77 |
4 | 89 |
5 | 80 |
6 | 92 |
7 | 91 |
8 | 102 |
9 | 106 |
10 | 130 |
11 | 155 |
12 | 160 |
13 | 180 |
14 | 199 |
15 | 240 |
16 | 305 |
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