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DS 4001 M1


Table of contents

  1. INTRODUCTION
  2. HYPOTHESIS
  3. SRC
  4. DATA
  5. FIGURES
  6. REFERENCES

INTRODUCTION

The question we explored pertains to how much of an impact graduating with a STEM (science, technology, engineering, and math) degree has on early-career salaries. On average, STEM majors earn $65,000, while non-STEM majors earn about $15,500 less. STEM majors were also more likely to be employed and hold only one full-time job, rather than a part-time job or multiple jobs [1]. In addition, STEM workers who majored in a STEM field in college typically made higher salaries than those who did not: on average, $101,100 vs. $87,600 [2]. According to a study of 159 college degrees by the personal finance company Bankrate, all 25 of its top-earning majors are ‘STEM’ majors [3]. Overall, it seems that STEM students, on average, make more money than non-STEM students.

For our project, we will focus on analyzing graduates of college and university in Virginia.


HYPOTHESIS

The United States early salary potential for graduates of public and private colleges and universities in Virginia is at least $5000 higher for colleges and universities that have a percentage of STEM students above or at 20%.


SRC

made-with-R

Installing/Building Code

First, one must make sure that R and RStudio are installed on their system. Then, you can download the script from our src folder, along with the dataset in the data folder. Make sure that the files are saved into the same directory and change the working directory to where the files are located. Finally, you can click run to view the outputs of the code locally.

Usage of Code

One would want to use our code to replicate and verify our results, or to possibly run further analysis on our dataset.


DATA

For full data, please click here

For the data dictionary, please click here

The first six rows of our data set are shown below...

rank name state_name early_career_pay mid_career_pay make_world_better_percent stem_percent
1 Auburn University Alabama 54400 104500 51 31
2 University of Alabama in Huntsville Alabama 57500 103900 59 45
3 The University of Alabama Alabama 52300 97400 50 15
4 Tuskegee University Alabama 54500 93500 61 30
5 Samford University Alabama 48400 90500 52 3
6 Spring Hill College Alabama 46600 89100 53 12

FIGURES

Figures Table

  • Scatterplot with Trend Line
  • Boxplot
  • Average Difference between Salaries
  • R-Squared Value and Significance Tests

Scatterplot with Trend Line

The graph shows a positive, linear, and moderately strong correlation between the two variables shown by the trend line. The confidence level is higher where the population is between 0% and 20%, since there are more data points compared to the low number of observations from the 20% to 40% population.

Boxplot

This plot measures the same two variables of early career pay and STEM populations at each school in VA. The boxplot below compares the two groups of STEM populations greater than or less than 20%. Key points are that the median salary for the less than 20% group is about $50000, and the greater than 20% group has a median salary of about $58000. This is evidence that helps support our hypothesis. Looking at the two groups, we can also see that the spread for the low STEM population group is higher. There are no outliers shown by the graphs.

Average Difference between Salaries

stem_percent > 20 average standard deviation
FALSE 51761 5852
TRUE 58400 7074

Descriptive statistics for Average and SD of Early Career Pay. Next, we computed the average pay and standard deviation for pay for each group. Although the averages support our hypothesis, the standard deviations are somewhat high.

R-Squared Value and Significance Tests

Value
R-Squared Value 0.5882328
P-Value 0.001983

Calculating R-Squared Value of the correlation and significance. Finding the correlation coefficient comes out to 59%. 59% of the variation in the early career pay variable is explained by the STEM population at each school. Testing Significance 1. Null hypothesis: variable 1 and variable have a correlation equal to 0. 2. Alternative hypothesis: variable 1 and variable 2 have a correlation not equal to 0. Running a significance test on the two variables, we found that the p-value was .001983. At a 95% confidence level, we can reject the null hypothesis that the correlation is equal to 0 as the p-value is statistically significant. The confidence interval is above 0, which supports the decision to reject the null hypothesis as well, although the range is quite large, likely due to the limited number of observations in the dataset. In conclusion, there is a significant relationship between early career pay and STEM populations in Virginia colleges and universities.


REFERENCES

[1] P. Jacobs, “Science And Math Majors Earn The Most Money After Graduation - Business Insider,” Business Insider, Jul. 09, 2014. [Online]. Available: https://www.businessinsider.com/stem-majors-earn-a-lot-more-money-after-graduation-2014-7. [Accessed: Sept. 14, 2022].

[2] U. C. Bureau, “Does Majoring in STEM Lead to a STEM Job After Graduation?,” The United States Census Bureau, Jun. 02, 2021.[Online]. Available: https://www.census.gov/library/stories/2021/06/does-majoring-in-stem-lead-to-stem-job-after-gr aduation.html. [Accessed: Sept. 14, 2022].

[3]“These are the degrees that will earn you the most money when you graduate - and the ones that won’t,” World Economic Forum. [Online]. Available: https://www.weforum.org/agenda/2021/10/stem-degrees-most-valuable/. [Accessed: Sept. 14, 2022].

[4] Mostipak, Jesse. “College Tuition, Diversity, and Pay.” Kaggle datasheet, 9 Mar. 2020. Available: https://www.kaggle.com/datasets/jessemostipak/college-tuition-diversity-and-pay?select=historical_tuition.csv. [Accessed: Sept. 14, 2022].

OTHER LINKS

  • Access our MI1 assignment from here 👋
  • Access our MI2 assignment from here 🤝

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