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Degrees That Pay You Back

Explore the salary potential of college majors with a k-means cluster analysis.

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Project Description

Wondering if that Philosophy major will really help you pay the bills? Think you're set with an Engineering degree? Whether you're in school or navigating the postgrad world, this project will guide you in exploring the short- and long-term financial implications of this major decision. After doing some data clean up, you'll compare the recommendations from three different methods for determining the optimal number of clusters, apply a k-means cluster analysis, and visualize the results.

This project assumes familiarity with standard tidyverse tools for R. While not required, it would also be helpful to have a prior understanding of clustering unsupervised data with k-means.

The dataset used in this project is made available here by the Wall Street Journal.

Project Tasks

  1. 1
    Which college majors will pay the bills?
  2. 2
    Currency and strings and percents, oh my!
  3. 3
    The elbow method
  4. 4
    The silhouette method
  5. 5
    The gap statistic method
  6. 6
    K-means algorithm
  7. 7
    Visualizing the clusters
  8. 8
    A deeper dive into the clusters
  9. 9
    The liberal arts cluster
  10. 10
    The goldilocks cluster
  11. 11
    The over achiever cluster
  12. 12
    Every major's wonderful

Technologies

R R

Topics

Data ManipulationData VisualizationMachine Learning

Prerequisites

Introduction to the TidyverseCluster Analysis in R
Jaclyn Burge HeadshotJaclyn Burge

Senior Data Consultant at The Walt Disney Company

Jaclyn has a degree in Cognitive Science from the University of California, Berkeley, where she helped teach The Beauty and Joy of Computing and worked on a tutoring startup. By day, Jaclyn is a fortune teller for The Walt Disney Company (in other words, she derives insights from data to forecast digital media consumption). By night, she is a competitive martial artist, an avid visual artist, and a voracious reader.
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