A Data Science Project Paper Overview

• Cover Page
• TOC
• Introduction
  • Describe the basics of your project, what question will you try to answer and what data will you look at.
  • This section should
    • Introduce anything the reader needs to understand to read the rest of the document.
    • Draw the reader in, invite them to continue reading.
  • Don't discuss meta-information about the project or paper. (ie this stuff)
• Data
  • Overview
    • Introduce your dataset.
    • Where did you get this data?
    • How much data is there (rows and fields)
    • If you will filter your data (remove some of the original dataset)
      • Briefly describe why you will filter the data.
      • Provide an overview (size in rows and fields) of the remaining data.
    • Describe the fields of interest.
    • Define any specialized terms associated with this dataset.
  • Data Dictionary
    • Provide a description of every field in the dataset.
    • This should be a well formatted table or a bulleted list.
  • Example Data
    • Give a few rows from the dataset
    • These should contain examples of valid data in all fields.
    • This should be one or more well formatted tables.
• Data Cleaning
  • If you decide to filter the data (not due to problems)
    • Discuss the reasons for filtering data
    • Discuss the rational for selecting the data you did.
    • Describe how you filtered the data (technical excel discussion)
  • For each problem you encounter with the data
    • Describe the problem.
    • Provide an example of bad/missing data
    • Describe how the problem will be mitigated.
    • Give a rational for fixing this problem the way you did.
    • Describe the actions taken in excel to mitigate the problem.
• Analysis of Fields Used.
  • This will depend on the field.
    • Numeric data should have at least a five number summary.
    • Some form of chart/graph to depict the data.
    • If you performed some computation on this data:
      • Describe that computation in sufficient details that a knowledgeable excel user could reproduce the computation.
      • This will include a written discussion.
      • It should include screen shots for any out of the ordinary computations.
• Methods
  • What did you do beyond basic analysis of the data?
    • Include a description of what you did.
    • Discuss why you did it.
    • Provide a description of how you did it in excel
      • Description and screen shots as required.
    • What did it yield.
  • Problems Encountered
    • What went wrong?
    • Why did it go wrong?
    • This is not a whining section.
      • You want to provide your reader with a guide to problems.
      • You want to document that you tried something that didn't work so they know not to try it
        • Or at least not try it the way you did.
    • Don't include
      • A discussion of how you didn't know how to use excel.
        • You will never completely know how to use a tool
        • They are too large
        • There are constantly new pieces added.
        • People discover new ways to do things.
      • A discussion of running out of time.
      • A discussion of what you did not know how to do.
  • Discoveries and Conclusions
    • Restate what you have learned/discovered.
    • State the question and discuss the answer based on what you have discovered/learned.
  • Future Work
    • Talk about things you would like to do but did not have time to accomplish
      • But don't say "I ran out of time, but I would like to ..."
    • New data you would like to collect to strengthen your study.
    • Other areas you would like to investigate.
  • Bib