BRYANT/SMITH CASE 32
WHAT FACTORS INFLUENCE PAYING BILLS ON TIME???
Ernest G. Hamilton III
Keller Graduate School of Management
GM 533 – Applied Managerial Statistics
December 14, 2010

INTRODUCTION
As you requested, the following information below illustrates my analysis in determining whether the dollar of a bill has an effect of the number of days the bill is late. Additionally, I have obtained information that determines if the bill is from a residential or commercial customer has any effect on the number of days the bill is late. The statistical analysis of the data includes regression analysis.
Data
The collection agency supplied a sample of 96 randomly selected customer bills. These bills demonstrate the following information: * One dependent variable (y), which is the number of days to collect the payment * Two independent variables (x1 & x2), which are the amount of the overdue bills and the specific type of customer accounts
Results
* The model depicts an average time of 50 days late for the bill * The average amount per bill was approximately $174 * According to the model, it suggests there is a correlation between the number of days the bill is late, the size of the bill, and the kind of customer account. * Analysis shows that when the size of the bill increases, the number of days the bill is late decreases, thus proving the relationship between the two variables is inversely proportional * Since the customer type coefficient is negative in the regression equation, it has an inverse effect on the number of days the bill is late * Regression equation: y = -0.0126x1 – 37.3958x2 + 70.6818
Our answer is dependent on whether or not the customer is a residential or commercial customer. When observing the data, we notice a decreasing trend between residential and commercial customers based on the number of