Bachelor's Degrees and Earnings

Posted on May 16, 2016

Contributed by Ismael Jamie Cruz. He is currently in the NYC Data Science Academy 12 week full time Data Science Bootcamp program taking place between April 11th to July 1st, 2016. This post is based on his second class project - Shiny (due on the 4th week of the program)

Joining the bootcamp allowed me to meet people from a wide variety of backgrounds including graduates from physics, computer science, finance, and architecture. In addition, there was diversity in origin with some classmates not only from New York but from the West Coast and other countries. With such a mix of people in one classroom, I became interested in how this looked like throughout the U.S.

I set out to explore datasets on bachelor's degrees (BD) with the curiosity of seeing educational attainment per state. My initial questions included what state had the most bachelor's degrees and how this looked depending on the field of bachelor's degrees. Like most data endeavours, these questions led to more questions, particularly with salaries of occupations that were degree-related. I wanted to see whether there was anything interesting relating bachelor's degrees and salaries in a particular state. I did this exploration through R and the Shiny package in order to develop an interactive web application.

Datasets

All datasets are from the U.S. Census Bureau, 2014 American Community Survey 1-Year Estimates, obtained through the American Fact Finder.

  • Field of Bachelor's Degrees for First Major for the Population 25 Years and Over (2014)
  • Educational Attainment (2014)
  • Occupation by Median Earnings in the Past 12 Months (2014)

The App

The Shiny web application or web app I designed shows three visualisations: bachelor's degrees as a choropleth, breakdown of bachelor's degrees, and earnings by occupation, both as bar charts. Bachelor's degrees per state are measured as a percent of the population. Breakdown of bachelor's degrees are also  represented as a percent while earnings by occupation are median figures. The app also has three features by which to manipulate the graphs. The user can choose the field of bachelor's degrees, the U.S. state, and the particular occupation.

The app can be accessed here.

Screen Shot 2016-05-16 at 4.37.01 AM

All Fields

Starting with all fields of bachelor's degrees (BD):

Screen Shot 2016-05-16 at 4.51.20 AM

  • Colorado (CO) has the highest percentage of state population with BD at 24.1% in 2014
  • Next two top states are Massachusetts (MA) and New Jersey (NJ) at 23.2% and 23.1%, respectively

Choosing state as CO:

Screen Shot 2016-05-16 at 5.04.40 AM

  • The breakdown of 2014 BD in the CO state in the snapshot above shows that Science and Engineering (SE) fields take majority at 39.2% followed by Arts and Humanities (AH) at 23.7% and Business (BU) at 19.2%
  • Similarly choosing MA, the breakdown of BD is as follows: SE at 39.1%, AH at 25%, and BU at 18.2%
  • Surprisingly, choosing NJ shows SE at 36.6% while AH and BU have a smaller spread at 21.2% and 22%, respectively

Moving on to occupations in CO:

Screen Shot 2016-05-16 at 5.13.57 AM

  • The snapshot above shows that top median earnings in CO in 2014 are from occupations classified as legal (LE), computer and mathematical (CM), and architecture and engineering (AE) with all slightly above $80,000
  • In the MA state, the top earnings by occupation turn out to be different and more spread out: LE at more than $100,000, followed by CM at $91,000 and health diagnosing and treating (HDT) at around $85,000
  • In the NJ state, the top is still LE at $97,000, followed by management (MGT) at $92,000 and CM at $91,000

The difference in earnings for similar occupations, such as LE, across states led me to wonder whether the amount of degrees in that state had a relationship with the earnings in a degree-related occupation. My hypothesis was that states that had a low amount of degrees in a particular field might have higher earnings in a degree-related occupation. The logic I thought was that a low supply of talent might see increased demand in the form of higher earnings. I was particularly curious to see this in the BU field.

Business Field

Choosing the business field of bachelor's degrees:

Screen Shot 2016-05-16 at 6.18.53 AM

  • States with the most BD in the field of BU seem to be in the east coast as seen by the predominant green color
  • The top states with the most BD in the field of BU as a percent of population include Florida (FL) and Georgia (GA)
  • The bottom states include Oregon (OR) and Wyoming (WY)

Earnings by occupation in GA:

Screen Shot 2016-05-16 at 6.28.44 AM

  • Looking into BU degree-related occupations such as management and financial, median earnings in 2014 were about $67,000 and $57,000, respectively

Earnings by occupation in OR:

Screen Shot 2016-05-16 at 6.31.30 AM

  • The earnings in the same occupations in OR show about the same figures at $66,000 and $55,000, respectively

Conclusion

Although it was interesting to see the breakdown of earnings by occupation for certain U.S. states, the graphs alone were not sufficient to answer my last question of whether there was a relationship between amount of bachelor's degrees as measured by percent of population and earnings in a degree-related occupation. For example, the comparison of business occupation earnings between Georgia and Oregon show similar figures despite having a big difference in business bachelor's degrees. Hence in order to dig deeper into my question I may have to proceed with some statistical analysis. In light of this, while the graphs are able to give a general idea about the distribution of bachelor's degrees in the U.S., further analysis is required in order to pursue deeper questions.

Questions for Future Analysis

Some questions I would like to explore for future analysis:

  1. Is there a relationship between amount of bachelor's degrees and earnings by degree-related occupation?
  2. How was the growth of educational attainment over time?
  3. How was the growth of earnings by occupation over time?

About Author

Ismael Jaime Cruz

Ismael’s roots are in finance and statistics. He has six years of experience in such areas as financial analysis, trading and portfolio management. He was part of the team that launched the very first exchange-traded-fund in the Philippines....
View all posts by Ismael Jaime Cruz >

Related Articles

Leave a Comment

No comments found.

View Posts by Categories


Our Recent Popular Posts


View Posts by Tags

#python #trainwithnycdsa 2019 2020 Revenue 3-points agriculture air quality airbnb airline alcohol Alex Baransky algorithm alumni Alumni Interview Alumni Reviews Alumni Spotlight alumni story Alumnus ames dataset ames housing dataset apartment rent API Application artist aws bank loans beautiful soup Best Bootcamp Best Data Science 2019 Best Data Science Bootcamp Best Data Science Bootcamp 2020 Best Ranked Big Data Book Launch Book-Signing bootcamp Bootcamp Alumni Bootcamp Prep boston safety Bundles cake recipe California Cancer Research capstone car price Career Career Day citibike classic cars classpass clustering Coding Course Demo Course Report covid 19 credit credit card crime frequency crops D3.js data data analysis Data Analyst data analytics data for tripadvisor reviews data science Data Science Academy Data Science Bootcamp Data science jobs Data Science Reviews Data Scientist Data Scientist Jobs data visualization database Deep Learning Demo Day Discount disney dplyr drug data e-commerce economy employee employee burnout employer networking environment feature engineering Finance Financial Data Science fitness studio Flask flight delay gbm Get Hired ggplot2 googleVis H20 Hadoop hallmark holiday movie happiness healthcare frauds higgs boson Hiring hiring partner events Hiring Partners hotels housing housing data housing predictions housing price hy-vee Income Industry Experts Injuries Instructor Blog Instructor Interview insurance italki Job Job Placement Jobs Jon Krohn JP Morgan Chase Kaggle Kickstarter las vegas airport lasso regression Lead Data Scienctist Lead Data Scientist leaflet league linear regression Logistic Regression machine learning Maps market matplotlib Medical Research Meet the team meetup methal health miami beach movie music Napoli NBA netflix Networking neural network Neural networks New Courses NHL nlp NYC NYC Data Science nyc data science academy NYC Open Data nyc property NYCDSA NYCDSA Alumni Online Online Bootcamp Online Training Open Data painter pandas Part-time performance phoenix pollutants Portfolio Development precision measurement prediction Prework Programming public safety PwC python Python Data Analysis python machine learning python scrapy python web scraping python webscraping Python Workshop R R Data Analysis R language R Programming R Shiny r studio R Visualization R Workshop R-bloggers random forest Ranking recommendation recommendation system regression Remote remote data science bootcamp Scrapy scrapy visualization seaborn seafood type Selenium sentiment analysis sentiment classification Shiny Shiny Dashboard Spark Special Special Summer Sports statistics streaming Student Interview Student Showcase SVM Switchup Tableau teachers team team performance TensorFlow Testimonial tf-idf Top Data Science Bootcamp Top manufacturing companies Transfers tweets twitter videos visualization wallstreet wallstreetbets web scraping Weekend Course What to expect whiskey whiskeyadvocate wildfire word cloud word2vec XGBoost yelp youtube trending ZORI