Simple Regression Pre-analysis (include ALL charts, graphs and tables you generate formatted to class expectations). Assume all variables (with the exception of the subject variable) are ratio level.
- YOU MUST HAVE the Data Analysis Tool Pack add-in installed to complete this assignment. Please review the notes for the week regarding how to use the Regression tool within the Data Analysis Tool Pack.
- Open the dataset associated with this assignment. Use New Capital Expense as the explanatory variable and End of Year Inventory as your response variable
- Generate a single Descriptive summary table in Excel of the explanatory and response variables. That is, simultaneously enter both variables into the Descriptive Statistic tool. Discuss the mean, median, standard deviation, range, kurtosis, and skewness for EACH variable. Please DO NOT JUST LIST THE numerical summaries. Discussion involves interpretation and should result in you writing complete sentences. See the exemplar, post to Moodle, for a sample writeup.
- Use Excel to calculate and the report the correlation number for these two variables. Interpret the result of the correlation number by discussing the linear strength and direction of the relation between the two variables.
- Use Excel to generate and report a scatter plot for the 2 variables. The Explanatory variable should be on the horizontal axis. Interpret the form and direction of the plot. Format plot to class expectations.
- Using only the visual inspection of the scatter plot, is a transformation warranted? Please review course notes and use what you notice about the dot pattern within the scatter plot as evidence to support your answer.
- Use the Data Analysis Tool pack to run the regression analysis to generate a residual plot for these variables. DO NOT INTERPRET NOR REPORT THE NUMERICAL SUMMARIES generated in the regression tables. Copy and Paste ONLY the residual plot into your report. Using only the visual inspection of the residual plot, is a transformation warranted? Review course notes and use what you notice about the dot pattern within the residual plot to support your answer.
- Check the 4 simple regression assumptions. Reference class notes so that you are clear what the checks should be and how to perform them in Excel. Create 4 subheadings to discuss EACH of the 4 assumptions indicating if the assumptions were met or were violated. Under each subheading, also include any tables or charts you’ve generated as evidence for your conclusions. Format all charts and tables to class expectations (see exemplar). Your claims regarding the assumptions must be based on content contained within the tables, numerical summaries , or charts that you generated. Please reference them by name in your write up. For instance “ It can be seen in Figure 1 ….” Etc …
- If any of the simple regression assumptions were violated, attempt to fix them using any combination of the 8 basic mathematical transformations (applied to either the explanatory or response variable or both) as presented in the notes for this week. Discuss in detail which transformation approach you decided to take and why. DO NOT SUBMIT the transformed dataset for grading. But, please report all charts or tables generated in Excel that you used to support your transformation efforts.