Post #3: Final Update – Literature Review/Project Summary

Hi everyone,

I have just completed revising and editing my completed Literature Review/Monroe Freshman research project, and I’m so excited to be submitting this to my project advisor soon! I haven’t kept her as updated as I hoped (through my own fault, though she agreed to be a more hands-off advisor), but I hope she enjoys reading the product. Thank you again, Professor Lopresti!

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College Sports Attendance & Gender – Final Update

First off, I took another approach to look at the data set. I used the controlled ratio I discussed in my previous post and compared the average value for basketball conferences. I took the average ratio for each conferences and then grouped the larger, well-known conferences known as the Power 6 (Big Ten, Big 12, SEC, ACC, Big East, Pac-12) and compared them to the smaller mid-major conferences. I would have done this for the other sports but basketball was the only one where almost all the schools had their men’s and women’s teams in the same conference. I’ve posted the graph below (found out how to make high-res pictures in RStudio, so now they’re a little more readable readable; any remaining issues I’m blaming on this site).

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Post #2: Completion of Reading, Outlining Literature Review, and Further Updates

Hello, everyone!

I am almost done with my research project, and I have been working hard this past month to complete my reading and plan out how I wanted to organize my literature review. I have read over 50 academic papers and had over 100 pages of notes, ranging from topics such as brand loyalty, advertising, the luxury goods markets across the globe in countries such as South Korea, Japan, Iran, and the U.S., the psychology of conspicuous consumption, and more. Consolidating all the information and choosing which papers/concepts were the most relevant to the motivation for my paper has taken a lot of thought, but I will outline below what my plan is for executing my literature review.

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College Sports Attendance & Gender – Update 2

So I decided to add a little more to the project than I had originally planned. Considering the website I was using to collect data had data all the way back from 2009, I thought seeing how differences were playing out over time would be interesting to see. I also decided to reevaluate the ratio I was using earlier. The way I was calculating ratios made comparisons between schools effective. However, the t-tests I was running were focusing on the differences between the men’s and women’s ratio. Programs that were large had a big difference between the ratios that implied that one program would be way more popular than the other, when actually the difference was fairly small relative to the attendance size. I decided for each school to divide the women’s ratio by the men’s ratio; value below one shows that the program attendance favors the men’s team; values above one favor the women’s team.

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