Provide a basic diagnosis of data problems using the tools


Proposal

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 three deliverables for this assignment spread over the term. This description refers to the first deliverable.

Detailed instructions for the first deliverable are listed below:

Detailed Instructions

During the live session in Module 1, I provided guidance on selecting a good dataset for your project. Data is plentiful these days, and a quick online search will yield many options. You can also use data from work or life. If you feel passionate about the data, you will have a great project.

Your project proposal should address three questions:

1. describe the dataset you would like to use, including the source of the data, how it was collected (if known), what the columns represent, and the size of the dataset

2. outline the question you would like to answer using the data

3. provide a basic diagnosis of data problems, using the tools you learned in Module 1. In the project deliverable #2 (Midterm), you will fix these issues. There is no need to fix your data for this assignment.

The proposal should be 1 to 3 pages of text, plus an Appendix that includes any JMP output you created for question #3. The write-up should be in PDF/Word/slides format. You should also upload a copy of the dataset, and any supporting materials such as a data dictionary.

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

1. You must include your name 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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Dissertation: Provide a basic diagnosis of data problems using the tools
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