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##DDS_401_TeamNI_Case_Study2

##Overview

This repository contains code written to explore and resolve Case Study #2 for the 401 (Winter 2018) term of the Doing Data Science course at Southern Methodist University’s Master’s of Science in Data Science. The purpose of this case study is to help a talent management firm study attrition rates for various career fields; more specifically, we will determine the top 3 (or more) variables that contribute to high turnover. We will also determine any other interesting trends we find in the data. We will accomplish this using exploratory data analysis and various machine learning algorithms using R, then publish the results using MarkDown.

##Team Members

Michael J. Wolfe

Ayoade Dare

##Key Files

CaseStudy2-data.csv -- Contains original data provided by DDS Analytics

DDS_401_TeamNI_Case_Study_2.Rmd -- Codebook containing analysis and exploration

DDS_401_TeamNI_Case_Study_2.html -- Report generated by aforementioned codebook

DDS401_TeamNI_Case_Study_2.pptx -- Supplemental presentation material

##Addendum

There is additional exploratory data analysis available on a public Tableau dashboard at the following link: