Stratford University Data Analytics Methods Presentation –

Stratford University Data Analytics Methods Presentation –

Programming –

1) Research Paper and Data Analysis Assignment

This research paper assignment will allow for you to select appropriate data analysis techniques and tools that are of interest to you. Your group will submit a detailed 8-page paper focusing on the following elements:

  • Part 1(7-8 pages)
    • Based on the Data Analysis methods covered thus far, select four data analysis methods.
      • For each method, provide a detailed overview of the purpose, strengths, and weaknesses of the method
        • identify at least 3 scenarios from research papers that show case each of these elements
          • identify how the way the element has been used can be improved.
  • Part 2 (2-3 minimum)
    • For two of the data analysis method, provide a detailed analysis using the data set(s) of your choice.
      • For example, if you have selected Naive Bayesian classification, then you should select a data set to accomplish this task.
        • Provide a detailed overview of your findings for each method and discuss the importance of using this method for your analysis.

Paper Requirements:

  • 8 -10 pages at a minimum
  • Your paper should be in 12 point Times New Roman Font, 1.5 space
  • Include at least 10 scholarly references (not websites, blogs, etc)
  • You will be graded on correct grammatical syntax and clarity!

Please cite your references in APA format. For each reference that you use please include an in-text citation. Your reference page does not count toward your paper requirement. DO NOT PROVIDE DIRECT QUOTES! You must summarize and synthesize in your own words.

2) Research Paper PowerPoint Presentation

  • Goal is to summarize your research paper
  • Minimum of 8-10 slides content (not including title and reference pages)
  • Must present for at least 10 minutes but no more than 15 minutes
  • All group members need to equally participate in the presentation

Our suggestion

Data Analysis Methods:

  1. Decision Tree
  2. Clustering : K-means
  3. Linear Regression
  4. Logistic Regression

Detailed Analysis:

  1. Linear Regression
  2. Decision Tree