CASE: 32 - Overdue Bills

CONTENTS

1) The Executive Summary
a) Describe the most important Facts and Conclusions.
2) Introduction
a) Purpose and Scope of Paper
b) Questions of Interest, and/or hypotheses
c) Describe the nature of the data set
3) Analysis and methods section
a) Interpret the statistical summaries
i) Tell the reader what you have found in the data (results, facts only). ii) Explain what those findings mean with regard to the problem (interpret results).
b) Design – describe the most important aspects of how the data was collected.
4) Conclusions and summary section
a) What has the analysis revealed? How have your questions been answered? (Refers back to the questions of interest, problem statement, and/or hypothesis
b) Why was the analysis done (Refer back to your background)
c) What of value was discovered? (Any unexpected results)
5) References
6) Appendix Executive Summary Based on my analysis I was able to determine that the size of the bill has an effect on the number of days the bill is late. I was also able to determine that commercial and residential bills get paid at different times based on the amount of them. We can also say that with the slope of .0166 (residential) means for each increase of one unit in X, the Y is estimated to increase .0166 units. On the other side the commercial business the slope of -0.191 for each increase of one unit in x, the Y is estimated to increase -0.191. The regression analysis for commercial represents 95.7% of our data, but we cannot say with 95% certainty that for residential customers that the size of the bill depends on when it gets paid.
Introduction
The background on the problem starts with the Quick Stab Collection Agency (QSCA) which collects bills in an eastern town. The company specializes in small accounts and avoids risky collection, such as those in which the