Quick Stab Collection Agency (Qsca) Collects Bills in an Eastern Town. the Company Specializes in Small Accounts and Avoids Risky Collections, Such as Those in Which the Debtor Tends to Be Chronically Late in Payments or Is Known to Be Hostile.
GM533
Course Project – Case 32
Executive Summary:
The purpose of this analysis is to assist the Quick Stab Collection Agency (QSCA) in determining if the amount or size of a bill collection is directly related to the number of days the bill is late. In order to support the validity of this relationship, a statistical analysis on the data provided will support the relationship with 95% confidence. These findings will give us a better understanding of the QSCA’s business and provide key insights on the relationships between the data being evaluated.
Introduction:
Determining whether the amount of a bill has an effect on the number of days the bill is late is the key focal point of this analysis. This information will be valuable for the business to develop efficiency and profitability within the account services team. In addition, the final output of the analysis can be applied to many situations, such as insights into customer trends in bill payment, 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 there management of bill acquisitions. We are currently faced with a challenging economy and our support of motivating clients to expedite their bill payments will help our business and our customer’s personal and internal finances.
To validate the relationship between the amount of a bill and the number of days late it is for both commercial and residential accounts, we apply a linear regression method to generate an accurate statistical analysis of the data. By using this form of analysis, we will be able to answer the following questions with the information provided. * Does the size of the bill somehow relate to the number of days the payment is late? If so, how? * Does the model show the correlation between the size of the bill and the number of days the bill is late? * Does the
Course Project – Case 32
Executive Summary:
The purpose of this analysis is to assist the Quick Stab Collection Agency (QSCA) in determining if the amount or size of a bill collection is directly related to the number of days the bill is late. In order to support the validity of this relationship, a statistical analysis on the data provided will support the relationship with 95% confidence. These findings will give us a better understanding of the QSCA’s business and provide key insights on the relationships between the data being evaluated.
Introduction:
Determining whether the amount of a bill has an effect on the number of days the bill is late is the key focal point of this analysis. This information will be valuable for the business to develop efficiency and profitability within the account services team. In addition, the final output of the analysis can be applied to many situations, such as insights into customer trends in bill payment, 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 there management of bill acquisitions. We are currently faced with a challenging economy and our support of motivating clients to expedite their bill payments will help our business and our customer’s personal and internal finances.
To validate the relationship between the amount of a bill and the number of days late it is for both commercial and residential accounts, we apply a linear regression method to generate an accurate statistical analysis of the data. By using this form of analysis, we will be able to answer the following questions with the information provided. * Does the size of the bill somehow relate to the number of days the payment is late? If so, how? * Does the model show the correlation between the size of the bill and the number of days the bill is late? * Does the
References: Bruce L. Bowerman, R. T. (2004). Essentials of Business Statistics. New York: McGraw-Hill Companies, Inc.