We started with Dr. Keiko Dow and Emilie Clark telling us about their experiences at the Nebraska Conference for Undergraduate Women in Mathematics. More info? See the post about it elsewhere on this blog.

Then we had three presentations:

Jaci Luisi: Urn models in probability

see http://blogs.canisius.edu/mathblog/wp-content/uploads/sites/31/2012/10/Oct10JL.pdf

Kristin DeRose: Bayes theorem, with examples

see http://blogs.canisius.edu/mathblog/wp-content/uploads/sites/31/2012/10/Oct10KdR.pdf

Jon Moreland: PageRank and eigenvalues.

see http://blogs.canisius.edu/mathblog/wp-content/uploads/sites/31/2012/10/Oct3JM.pdf

Bayes Theorem talk:

Kristin’s presentation on Bayes Theorem was interesting. She clearly explained the theorem and then used it to solve real world problems. The presentation included nice visuals and the simulator of the Monty Hall problem was helpful. I’m familiar with Bayes Theorem from MAT 351 with Kuhlmann last semester, but Kristin showed different applications than those I learned in class. The Monty Hall problem was very intriguing and not too difficult to understand, so I’m sure that people without a probability background understood it well. I think I’m ready to go on a game show now!

PageRank talk:

Jon’s talk on PageRank was interesting to me because it showed one of the many real world applications there are for mathematics. It’s really nice to know that some people can make a ton of money through their math skills. What else was interesting was that PageRank was a probability distribution but Jon showed that there is linear algebra involved. When I took Linear Algebra I felt that it wasn’t really that applied to the real world so it was nice to see an example of that.

Jon’s presentation on PageRank was very interesting. In one of my computer science courses last semester, we implemented the PageRank algorithm in a Java application, so I became very much acquainted with the coding techniques used in creating the algorithm. Having this base knowledge, I found it particularly interesting to learn more about the mathematics that drive PageRank. Jon did a great job presenting the material. By occasionally stepping back to ask the audience for their input, he developed an intriguing and interactive presentation. I found the example on the chalkboard to be quite helpful because I was able to follow along at a better pace than if he were to display the full solution on a slide.

Kristin did a great job with her talk on Bayes’ Theorem. We covered the theorem in MAT 351 last semester, but I found it very beneficial to learn more about its various applications. She clearly demonstrated the significance of the theorem through the many examples provided. We considered the Monty Hall Problem last semester, and Kristin’s presentation was a nice supplement to my previous understanding of the simulation. The talk was further enhanced by the inclusion of the simulation website. After discussing the theory in detail, it was great seeing the simulation in action!