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Regression

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The manager of the purchasing department of a large banking organization would like to develop a model to predict the amount of the time it takes to process invoices. Data are collected from a sample of 30 days, and the number of invoices processed and completion time, in hours,is stored in the file INVOICE.xls(see attachment).
(Hint: first determine which are the independent and dependent variables.)

a) Assuming a linear relationship, use the least-squares method to compute the regression coefficients B0 and b1.
b) Interpret the meaning of the Y intercept, B0, and the slope, B1, in this problem.
c) Use the prediction line developed in (a) to predict the amount of time it would take to process 150 invoices.
d) Determine the coefficient of determination, r square(r*r), and interpret its meaning.
e) Plot the residuals against the number of invoices processed and also against time.
f) Based on the plots in (e), does the model seem appropriate?
g) Compute the Durbin-Watson statistics and, at the 0.05 level of significance, determine whether there is any autocorrelation in the residuals.
h) Based on the result of (e) through (g), what conclusions can you reach concerning the validity of the model?

Use Excel or PhStat 2 (Excel Extension program)

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