MSDS 430 Python For Data Science

MSDS 430 Python for Data Science
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Assignment:
The goal of this last piece of your project is to tie everything together from Phase 1 and Phase 2 into a managerial style report. Approach this assignment by assuming you are formally presenting your findings to your manager in report form. Throughout your report, you should assume your manager does not have any programming background but does have some basic knowledge of EDA.

Your report should describe the data chosen and list the resource where it was found, plus why this particular data set was chosen. Without going into the technical aspects of how the data was ‘cleaned’ in Phase 1, briefly describe what was done to make the data easier to work with. In addition, your report should explain the steps taken in Phase 2 to complete the 2nd phase of EDA.

In particular, describe what hypotheses or conjectures you ended up testing and why. In basic terms, explain what calculations you performed to confirm or disprove your hypotheses and why. This portion of your report should include your graphs and what the graphs are portraying. End your report with any conclusions made from your analysis. List any (nontechnical) difficulties you encountered and possible ways to improve the outcome(s). Additionally, list other aspects of the data you would be interested in pursuing in the future. A general recommendation for the length of your paper is 3 – 5 pages not including the title page and any appendices. Submit a PDF file of your report. No other files are needed.
Grading Rubric:
Paper structure – 5 points ·
Paper contains title page, name on paper, page numbers, section headers
Writing Quality – 5 Points
Proper sentence structure, Clear communication of concepts

Flow of concept is easy to follow Introduction – 20 points 

Provide an overview of your project relative to your specific goals

Explain why this project was important to you

Describe the source of your data

Explain the hypothesis (or hypotheses) you set out to test. What hunch(es) did you have about the data that made you interested in the data?
What question(s) were you hoping to answer with this data?
Data Preparation And Analysis – 50 Points
Provide an overview of the data – consider the data dictionary you provided in Phase 1 
Explain the steps taken to prep and clean the data
Were there missing data and outliers you had to handle? 
Explain your calculations · Analysis of data – include visuals
Explain any insights gained
Conclusion – 20 Points
Interpret the results
Were there any difficulties with data or project as a whole? 
Provide your conclusions · What are some possible next steps?