The project: Using records of alumni donations provided by Williston’s Advancement Office, Ms. Andrews analyzed the data to explore the significance of various factors in predicting how much an alum will give over a lifetime, when an alum will make a first gift, and how many gifts an alum will make. She examined variables such as graduation year, where alums live, gender, and whether they were day or boarding students. “I wanted to analyze data that was not from a textbook, to familiarize myself with what statistics will be like in a professional, research setting,” she notes. “I chose data from Williston so I could influence the local community.”
From her report: “I am passionate about data analysis. For my project, I learned how to organize raw data in excel, perform significance tests, and determine the appropriate visual representations to display relationships. I did not have much experience with Excel or MiniTab when I began my project. I enrolled in Williston Scholars because it was a great opportunity to learn how to apply what I have learned about statistics to real data. I learned how to use computer programs to determine if various factors could be predictors for lifetime giving amount and number of gifts. I gained experience in structuring an analysis and deciding what is practically important for advancement.”
Biggest challenge. “The Advancement Office gave me over 8,000 data points, so I was kind of intimidated. I had never worked with that large of a data set. But that was why I did Williston Scholars, to get out of my comfort zone and get that experience. Another challenge was to organize what tests I was going to perform to see what factors were relevant or significant to alumni donations. I ended up doing a big concept map that really helped me organize things, and sitting down with my AP Statistics teacher, who is also my advisor, Miss Baldwin, really helped me organize my thoughts and decide what tests would be correct and accurate.”
Surprising discovery. “A surprising discovery is that state is not significant in alumni donations. So where an alum lives cannot predict how much they will give back to the school. That was the thing I was most focused on. I was looking forward to making this map with this excel add-in and seeing, oh, everyone is in the northeast, and the closer you live to the school the more you give, you know? But it turns out, it’s not significant, and that was good because it really pushed me to look at other factors, like gender and boarding/day.
Tip for future scholars. “Try to decide what you are doing as soon as possible. I got a lot of help from my dad and my teacher, Mrs. Hill, and they both helped a lot in narrowing down what I was going to look at, and suggesting what I should be focused on. I didn’t want to have to gather all the data. That would take so long. I got the data so soon in the trimester that it was really easy to focus just on analysis. So, focus on what you want to learn the most. I’m more interested in data analysis than I am in sampling method design stuff.”