Gm533 Project

INTRODUCTION

The purpose of this analysis is to analyze the QSCA in determining if the amount or size of a bill is directly correlated to the number of days the bill is past due. In order to support the validity of this relationship, a statistical analysis of the data provided will support the relationship within 95% confidence levels. These findings should give a better understanding of the QSCA’s business and provide vital insight on the relationship between the data being evaluated.

SUMMARY

The focal point of this analysis is to determine whether or not the amount of the bill has an effect on the number of days the bill is late. This information will be extremely valuable for the business to develop higher efficiency and profitability within the account services team. In addition, the final output of the analysis can be applied to several situations, such as insights into customer trends like bill payments, financing, and the current economic impact on the bill collection business. This analysis will help confirm the importance of paying a bill on time and should be supported by the client services team in the management of bill collection. We are currently face with challenging economic times and the support of motivating clients to expedite their bill payments will help businesses and customer’s personal and internal finances.

In order to validate the relationship between the amount of a bill and the number of days late for both commercial and residential accounts, we must apply a linear regression method to generate an accurate statistical analysis of the data presented. In using this form of analysis, we must be willing to answer the following questions:

1. Does the amount of the bill correlate to the number of days the payment is delinquent? If so, how?

2. Does the relationship between the days late and the amount of the bill differ between commercial and residential accounts?

3. Does the model show the correlation between the size of the...