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Student Projects

Visualizing Public Health

Authors: Mele Sato, Sirena Van Epp, Judy Wu

Grade: 11th

Subject: Math

Colorful chart with number of nuclear reactors in given states
Project details
Poster: Collegiate Retention Conference
Poster: Child obesity rate per state
Group shot outside of HTHMA

More and more our world is influenced by data. Data is embedded throughout our daily lives, informing our decisions whether we are aware of it or not, and empowering governments and organizations to delegate funds and resources from San Diego County to nations around the world. This project allowed students to explore methods of data collection, analysis, and research into public health at a local and global level. Public Health professionals produce factsheets that inform audiences from those who make policy decisions to a young mother visiting a local clinic because she is concerned about her child’s health.

In this project students were guided by a series questions. The explorations, classwork, homework, and project components directly related to and helped the students answer these questions.


  1. What can data tell us?


  1. Making sense of data.
    • Discussion of basketball players: What made this assignment difficult? What were some limitations?
    • Mean, Median, Mode Line-up
    • Mean, Median, Mode Practice #1
    • SAT Math corners


  1. How do we know “good data” when we see it?
    • Speed dating with statistics: Students found visualizations of data online about any topic of their choice and shared it with other students.
    • Headlines Chalk Talk Gallery Walk: Students wrote down headlines from the news that made claims based on data or had data in them. They wrote them on the desks and we did a gallery walk asking questions about what we would expect or hope to see in the article that followed.


  1. What does data look like?


  1. How is statistics manipulated and interpreted?


  1. What is an indicator? What makes a sample space significant?


  1. How is data analyzed? Making sense of data analysis in social contexts.


  1. What tools do we need to do research in social contexts?


  1. What does a public health professional do?


  1. What indicators do we need to consider in answering our research question?


  1. What kind of analysis can be performed on our data?

What are the big problems facing humanity and our local and global communities? How can we tackle these issues and communicate what we learn with the public? What does all this data mean? How do you interpret data and graphs? What now?

Public Health Factsheet. Factsheets are a central part of how public health professionals communicate their findings, analysis, and recommendations to the general public, government and non-governmental organizations, and nonprofit organizations. The audience and distribution change the content and layout of each factsheet.

Data Visualization. This visualization is not a graph in the traditional sense but rather a way of “seeing data”. A well-done visualization is a polished piece of work that is created using digital media, done by hand, or a constructed piece of work. It should provoke questions and observations from the audience without including any conclusions or telling the audience what to think or see.

  • Measures of central tendency: mean, median, mode, standard deviation, lower and upper quartiles
  • Correlation vs. causation
  • Regression line analysis
  • Other forms of analysis based on the sample space and results
  • Google sheets or Excel
  • Access to internet databases of public data
  1. Expert interviews: Local public health professionals, teacher’s sister who is the Peace Corps representative for PEPFAR (President’s Emergency Plan For Aids Relief)
  2. Real data is gathered through government and non-governmental sources
    • International Demographic Data through GapMinder
    • Google’s Public Health Database
    • California Department of Public Health
    • San Diego County of Public Health
    • Centers for Disease Control (National Data)
    • International Census Data
    • National HIV Behavioral Surveillance
  3. Make predictions and consider trends in the data given the statistical analysis performed on their indicators. Make recommendations to their target audience on how to move forward.

The birth of this project was a phone conversation with my sister, who has worked in the public health field, in various capacities, for the past six years. Through sharing her experiences in the Peace Corps, research in graduate school, and different positions held for health related government organizations, I learned about a new field where math had a very powerful, social, and global impact on people’s lives. I immediately wanted to share that epiphany with my students and have them experience the power math has to change people’s perspectives and create change. Using real data from government and non-government organizations students chose indicators and issues they were passionate and concerned about. Examples include expulsion rates, drug use amongst teenagers, teen pregnancy, vaccination rates, and the zika virus. I really enjoyed doing research with my students and discussing the impact and implications of their data analysis.

This project stood out because it felt a lot more “real world” than most projects. I know that’s usually the goal for most everything we do at this school but I feel like this one was executed very very well. The most memorable thing about this project was all of the shocking statistics we found on topics that interested us. When the students are looking at things they’re interested in, the motivation goes up and the products are always of better quality. Something that was challenging about this project was that we had to find our own data, which turned out to be much easier said than done. This challenge really made this project unique and made it more meaningful because we had to do all the dirty work dealing with the numbers and it made what we found so much more rewarding. Statistics mean so much more when you are the one who takes the time to find the data yourself. – Julia Rosecrans ‘17