# Case 32- Overdue Bills

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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…show more content…
(Figure E) Some other questions that I am going to answer that support my main problem are whether or not the type has anything to do with how late a bill get paid. Analysis and Methods Based on the data the dependant (response) variable is the days overdue which is represented in Figure E as Y. The independent (predictor) variable is the bill amount and the type of bill which are represented by X in Figure. In analyzing all the data I was able to conclude that we did not need the type in the regression analysis, so based on that conclusion the following analysis are what I based my report on: A) 1st Analysis – Overdue Bills Commercial a. Scatter Plot Shows: Figure A i. The higher the bill the less overdue it is, and the lower the bill the more overdue it is b. The scatter plot follows the straight line – this scatter plot has a negative linear relationship. c. Regression Analysis: Figure B i. Days = 101.7582 – 0.1910 * Bill ii. 95.7% of the data can be explained by using the commercial data with the independent variable of Bill. iii. The slope of -0.191 for each increase of one unit in x, the Y is estimated to increase