Case 32- Overdue Bills
1) The Executive Summary
a) Describe the most important Facts and Conclusions.
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…
b. Regression Analysis: Figure D
i. Days = 2.2096 + 0.1657 * Bill ii. 93.3% of the data can be explained by using the commercial data with the independent variable of Bill. iii. The slope of .0166 (residential) means for each increase of one unit in X, the Y is estimated to increase .0166 units.
The data was collected through megastat using the correlation/regression menu item, under their I used scatter plot diagrams to show the line of mean and to give a visual of what I saw and then I did a regression analysis to show the p-values and r factors.
What this means in regards to our problem is that yes, you can determine with a 95% confidence interval that the overdue bills (commercial) is dependent on the size of the bill. In this case the higher the bill the quicker it got paid and the lower the bill the longer it took to get paid. This regression analysis represents 95.7% of our data. Now on the flip side with overdue bills (residential) we cannot say with 95% certainty that the size of the bill depends on when it gets paid but we can say that the lower the bill the faster it gets paid and the higher the bill the longer it gets paid.
Conclusions and Summary In conclusion the analysis has proven that it does depend on the size of the bill as to when it gets paid; it has also