Assignment 9

In this assignment, you will use R (within R-Studio) to:

• Load and clean a real data set
• Conduct exploratory analyses, including informative figures
• Build and test appropriate models
• Draw conclusions about your data
• Combine all of the above into a well-documented R-Markdown report and export (knit) it into an HTML file

All file paths should be relative, starting from your Assignment_9 directory!!

This means that you need to create a new R-Project named “Assignment_9.Rproj” in your Assignment_9 directory, and work from scripts within that.

For credit…

1. Push a completed version of your Rproj and R-markdown file (details at end of this assignment) to GitHub
2. Your score will also depend on your analyses and presentation of your final report

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Your tasks:

• Use the data set “/Data/GradSchool_Admissions.csv”
• You will explore and model the predictors of graduate school admission
  • the “admit” column is coded as 1=success and 0=failure (that’s binary, so model appropriately)
  • the other columns are the GRE score, the GPA, and the rank of the undergraduate institution, where I is “top-tier.”
• Document your data explorations, figures, and conclusions in a reproducible R-markdown report
• That means I want to see, in your html report, your process of model evaluation and selection. Here’s an example
• Upload your self-contained R project, including knitted HTML report, to GitHub in your Assignment_9 directory