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A key feature of this course is applying learning to a real-world dataset. The project takes you through all the steps of a typical data analysis project over the course of the semester. There are two deliverables for this assignment. This description refers to the second and final deliverable.

Note that this project is completed with a partner.

Detailed instructions for deliverable 2 are listed below:

Deliverable 2 is the final project submission. For this deliverable, your starting point is the analysis dataset from Deliverable 1. Based on the question you have outlined for your dataset, you should work with your partner to select an analytical methodology to solve that problem.

You should choose a methodology that is covered in the course. If you intend to use some other methodology, you must first obtain permission from the instructor or facilitator.

In some cases, your instructor or facilitator may have offered additional ideas about data cleaning as part of the feedback to your Midterm submission. You should fix those additional issues as part of this assignment.

Modeling is an iterative exercise, and it is possible that you will learn some things during this assignment that will suggest further data processing. If you do take these steps, you should indicate the additional work you have undertaken in your write-up (the appropriate place for this will be in the Appendix).

The Final deliverable should be consist of three parts:

• The document deliverable
• R code
• Data/sample data.

The document deliverable should consist of 3 to 5 pages of text, plus an Appendix that includes any R output to support your conclusions.

The write-up should be in PDF/Word/slides format. The write-up should address the following questions, in this prescribed order:

1. What is the recommended action and how do you expect the action to affect business or organizational goals?

2. What are the conclusions of your data analysis that support your recommendation?

3. What is the basic concept of the methodology you selected for the analysis, and what are its strengths and weaknesses?

Remember: the audience for your write-up are business managers. You should focus on business issues. Technical details can be discussed in the Appendix, if you so wish.

You must submit to this assignment page by the due date and time listed on the top of this page. You should upload all your files to Canvas. Emails will not be accepted.

Important: here are formatting guidelines you should follow, which should be standard in a workplace.

1. You must include both of your names on the first page of your write-up, as well as in the name of the file you upload.

2. Include page numbers

3. Make sure you explain any acronyms or industry jargon. Remember that your instructor/facilitator may not know much about the context of your dataset.

4. If you are including images of data, make sure the font size is humanly readable.

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