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Project Part Three - Automating Business Processes

Project Part Three

Automating Business Processes                   

Professor: Keeling

 

This assignment should be completed individually. This is the final portion of your class Project.

Project Part Three Goals:

1.     REPORT: Explore three research questions that you want to answer with your data by comparing means and performing regressions. (Note: Different should be RQ from project part 2)

2.     MENU: Using Python, import your two csv files and create a menu of choices and perform summaries, graphs, and statistical tests based on user inputs.

3.     PRESENTATION: During our final exam time on Monday November 18th, you will demo your Menu to your fellow students. You will demo 3 or 4 different times as we rotate in small groups.

Programs: For your menu and your report, create separate Python Notebook files that are formatted nicely (use markdown to label the major portions of your code.)  The code should not have any "hard coded" paths but instead should easily run from my machine if I have this notebook file and your 2 data files located in the same folder on my computer.

Requirements:

MENU:

         You must have at least 8 menu choices plus 1 quit option.

         The output for these can overlap with your research questions for project part 2 and 3 or can be new output/analysis.

         At least one menu choice must output a regression.

         At least one menu choice must output a t test or ANOVA.

         At least one menu choice must output a graph (not including what you might get from the above).

         At least one menu choice must output something to an Excel file.

         At least 3 of your menus must allow the user to make a filtering choice (e.g., a certain variable or a certain category of a qualitative variable)

REPORT:

         THE PROBLEM:

o    List at least 3 research questions that you want to explore with your data. These research questions should be able to be answered by comparing means (t tests or ANOVA) or regressions.

         THE DATA:

o    Read in your 2 csv files and merge the data together into a single pandas DataFrame. Make sure your DataFrame columns have the correct types.

         THE ANALYSIS:

o    For each research question, include in this section

  The research question

  The analysis

  Your conclusion about this research question

         THE CONCLUSION:

o    Include an overall conclusion about your data and research questions

PRESENTATION:

         Be prepared on Monday November 18th to demonstrate your menu code to 2 or 3 others in the class at a time in a "round robin" fashion. You will basically talk through your code and then have your audience help you choose your menu options and the "subfiltering" questions. Plan for your demo should take 4-5 minutes.

Submit (two separate submissions): a zipped file containing your .csv files and your .ipynb file. Please create zip files and not any other compressed type of file.

Project Part 3 Combined rubric

Project Part 3 Combined rubric
Criteria Ratings Pts
This criterion is linked to a Learning OutcomeImport CSV Files and run smoothly for instructor 15.0 pts Full Marks 0.0 pts No Marks 15.0 pts
This criterion is linked to a Learning OutcomePython Notebook Formatted Nicely 10.0 pts Full Marks 0.0 pts No Marks 10.0 pts
This criterion is linked to a Learning Outcome8 or more menu choices plus quit...menu runs until quit is chosen 15.0 pts Full Marks 0.0 pts No Marks 15.0 pts
This criterion is linked to a Learning OutcomeAt least one Regression 10.0 pts Full Marks 0.0 pts No Marks 10.0 pts
This criterion is linked to a Learning OutcomeAt least one 2 sample t test or ANOVA 10.0 pts Full Marks 0.0 pts No Marks 10.0 pts
This criterion is linked to a Learning OutcomeAt least one graph (not from t test or ANOVA) 10.0 pts Full Marks 0.0 pts No Marks 10.0 pts
This criterion is linked to a Learning OutcomeAt least one command that writes something to Excel 10.0 pts Full Marks 0.0 pts No Marks 10.0 pts
This criterion is linked to a Learning OutcomeAt least 3 choices that let a user filter the data This could be a filter restricting analysis to one column or one or more values in a column. 10.0 pts Full Marks 0.0 pts No Marks 10.0 pts
This criterion is linked to a Learning OutcomeProblem Statement Give a summary of the goal for your 3 research questions. 5.0 pts Full Marks 0.0 pts No Marks 5.0 pts
This criterion is linked to a Learning OutcomeResearch Question 1 clearly stated 10.0 pts Full Marks 0.0 pts No Marks 10.0 pts
This criterion is linked to a Learning OutcomeAnalysis for Research Question 1 Python code 10.0 pts Full Marks 0.0 pts No Marks 10.0 pts
This criterion is linked to a Learning OutcomeResearch Question 1 Python Code output 5.0 pts Full Marks 0.0 pts No Marks 5.0 pts
This criterion is linked to a Learning OutcomeResearch Question 1 Conclusion In your own words. 5.0 pts Full Marks 0.0 pts No Marks 5.0 pts
This criterion is linked to a Learning OutcomeResearch Question 2 clearly stated 10.0 pts Full Marks 0.0 pts No Marks 10.0 pts
This criterion is linked to a Learning OutcomeAnalysis for Research Question 2 Python code 10.0 pts Full Marks 0.0 pts No Marks 10.0 pts
This criterion is linked to a Learning OutcomeResearch Question 2 Python Code output 5.0 pts Full Marks 0.0 pts No Marks 5.0 pts
This criterion is linked to a Learning OutcomeResearch Question 2 Conclusion In your own words. 5.0 pts Full Marks 0.0 pts No Marks 5.0 pts
This criterion is linked to a Learning OutcomeResearch Question 3 clearly stated 10.0 pts Full Marks 0.0 pts No Marks 10.0 pts
This criterion is linked to a Learning OutcomeAnalysis for Research Question 3 Python code 10.0 pts Full Marks 0.0 pts No Marks 10.0 pts
This criterion is linked to a Learning OutcomeResearch Question 3 Python Code output 5.0 pts Full Marks 0.0 pts No Marks 5.0 pts
This criterion is linked to a Learning OutcomeResearch Question 3 Conclusion In your own words. 5.0 pts Full Marks 0.0 pts No Marks 5.0 pts
This criterion is linked to a Learning OutcomeOverall Conclusion Summary of what the three questions really mean. 10.0 pts Full Marks 0.0 pts No Marks 10.0 pts
This criterion is linked to a Learning Outcomecompressed (zip) file contains all the files needed 5.0 pts Full Marks 0.0 pts No Marks 5.0 pts
Total Points: 200.0

Project Part Three - Automating Business Processes

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