Question

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.

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

Answer 1

Lets understand the Impact of Cash Balance through Moving Averages
Moving Averages- Basis 2 Years
Month	Cash Balance
1	75	72.5
2	70	73.5
3	77	83
4	89	84.5
5	80	86
6	92	91.5
7	91	96.5
8	102	104
9	106	118
10	130	142.5
11	155	157.5
12	160	170
13	180	189.5
14	199	219.5
15	240	272.5
16	305
When We look at the cash Balance based on two years Average, there is consistent increase over 16 years
Based on the above, we can conclude that company will not suffer cash crunches
Now Lets calucalate Moving Averages- Basis 3 Years
Month	Cash Balance
1	75
2	70	74
3	77	78.66667
4	89	82
5	80	87
6	92	87.66667
7	91	95
8	102	99.66667
9	106	112.6667
10	130	130.3333
11	155	148.3333
12	160	165
13	180	179.6667
14	199	206.3333
15	240	248
16	305
When We look at the cash Balance based on three years average, there is again consistent increase over 16 years
From the above calculations, we can assume that the company will not suffer cash crunches for the years to come
Now Lets calucalate Moving Averages- Basis 4 Years
Month	Cash Balance
1	75
2	70
3	77	77.75
4	89	79
5	80	84.5
6	92	88
7	91	91.25
8	102	97.75
9	106	107.25
10	130	123.25
11	155	137.75
12	160	156.25
13	180	173.5
14	199	194.75
15	240	231
16	305
When We look at the cash Balance based on four years average, there is again consistent increase over 16 years
From the above calculations, we can assume that the company will not suffer cash crunches for the years to come
Final Conclusion: The Companies Cash Balance will be adequate to render the services