Underrepresented Populations to Space

Inspiration

During our data exploration phase, we noticed an astronomical discrepancy between men and women in space. The ratio of male to female astronauts was about 7:3, which indicates a need for change. We took the time to explore current gender gaps in the astronaut field, and where these discrepancies stem from in post-secondary education.

What it does

Our project takes a data-backed approach to the gender gap in space. Our data analysis, combined with research by experts in the field, provides a well-rounded perspective on why women are underrepresented in this field, future projections for the gender gap, and what we can do to address this.

How we built it

We employed Python libraries (Pandas, NumPy, Seaborn, and Matplotlib) and Excel to clean, analyze, and visualize our data. Our final presentation was designed using Google Slides.

Challenges we ran into

Our main challenge was finding a story in our data. Part of the challenge with this track was that the dataset was limited in size and features. However, once we found our supplemental datasets we were able to understand our subject more and find gaps in the field.

Another challenge was specifically with our IPEDS data, as there was no raw data source we could download. We instead manually inputted the data into excel and cleaned from there. It was difficult formatting and figuring out the data.

Accomplishments that we're proud of

We are proud of our polynomial regression model, as it conceptualizes the issue at hand really well. We are also proud of how we used Python to run statistical tests for the first time.