Statistics Student Wins Second Place in National Undergraduate Statistics Project Competition

February 26, 2015

Jimmy Wong with a sample of the data analysis he produced using the statistical software package called R.

Jimmy Wong has been busy. Over the last year, the senior statistics major has programmed apps for statistics education, presented at national conferences, and worked on research projects with two professors. Not to mention winning second place in the National Undergraduate Statistics Project Competition.

The competition is sponsored by the Consortium for the Advancement of Undergraduate Statistics Education, which is made up of colleges and universities across the country. Wong's winning project focused on his analysis of data from a National Science Foundation-funded project investigating ways to make statistics more accessible to a wider audience.

The study focuses on a new, hands-on curriculum for an introductory statistics course that was piloted at 20 institutions during 2013-14. In this curriculum, students actively discover statistical concepts rather than simply memorizing formulas. For example, students can have a computer perform a set of 30 coin flips 1,000 times to assess whether a certain result could plausibly have happened by chance alone, The faculty members developing the curriculum want to know whether it works, and that's where Wong's analysis comes in.

"Jimmy analyzed conceptual understanding and student attitudes before and after the course to help measure its effectiveness," said Beth Chance, a statistics professor and Wong's advisor.

The data analysis is ongoing, but Wong's work provided a foundation for future researchers. "Jimmy got to learn about this type of data analysis that he never would have seen before graduate school. He programmed a new interface in R [a statistical software package] that showed how useful this tool is for educational and other types of multi-level data," Chance said.

"When I was working with Dr. Chance, I was completely new to the analysis method," Wong said. "I had to learn not only the method itself but also how the data was collected, how to implement the analysis, and how to clean the data. It was a really hands-on learning experience."

Wong took this experience and is using it to program apps that can be used to help students visualize different types of statistical analysis.

"I think my experiences at Cal Poly are really relatable to the real world," Wong said. "In the future, if I get data that requires a method that I'm not familiar with, I have that experience of learning and doing research independently."

Wong plans to pursue a doctorate in statistics and data science after graduation.