Forty-Fifth Annual
State of Jefferson Mathematics Congress
September 30 — October 2, 2016
Whiskeytown Lake, CA


A User-Friendly Derivation of E = mc² by Rick Luttmann, Sonoma State University.

Einstein's famous formula quantifies the equivalence of mass and energy. But when Einstein proposed it in his 1906 paper, he wasn't thinking of mass-energy conversion, a phenomenon not then known or even suspected. He was merely trying to update the classical physics formula for Kinetic Energy to allow for the new and counter-intuitive conclusion which his remarkable Theory of Relativity predicted: that mass, time, and distance are not absolute and objective but depend on the speed v (relative to the speed c of light) between the observer and the observed via the factor 1−(v/c. We look at the derivation of both the old and the new Kinetic Energy formulae and sketch briefly where the 1−(v/c factor comes from. [Lecture Notes]

Paradoxical Elections and Voting Theory by Randall Paul, Oregon Institute of Technology.

There are many different ways to determine the winner of an election when there are three or more candidates. Plurality and run-off elections are the most common, but various methods using preferential ballots (where candidates are ranked) also occur. It is generally assumed that in all but the most closely contested races all of these methods will elect the same "most popular" candidate. Voting theory tells us that this assumption is false — the clear winner by one method can easily lose badly by another method. We look at how these "voting paradoxes" occur, as well as how mathematics can help us judge the relative merits of different methods.

Discussion Under the Oaks — Flipped Classes, Open Source Textbooks, and Creating Significant Learning Experiences led by Larry Shrewsbury, Southern Oregon University.

SOU was one of 44 universities chosen to participate in the "Reimagining the First Year of College" program — the idea of which is to review, adopt and share practices, programs and implementation strategies aimed at improving student success. One part was to redesign our "Introduction to Statistical Methods" course (MTH 243) to improve the student success rate. To me, "success rate" means that significantly more of our students who finish our MTH 243 will retain that knowledge and successfully apply it in future coursework. This past year has been a wild (and wonderful) ride; this is what I've learned, and what I'm going to be trying out this next year.



Kelso Quan Chico State
Shannon Hussey Chico State
Steve Samons Chico State
Thomas Mattman Chico State
Kyle Falbo College of the Redwoods
Caleb Hill Humboldt State
Jeff Haag Humboldt State
Ken Yanosko Humboldt State
Walden Freedman Humboldt State
George Lowe Mayland
Dibyajyoti Deb Oregon Tech
Kathryn Rooney Oregon Tech
Kenneth Davis Oregon Tech
Randall Paul Oregon Tech
Andres Anlas Salman Sacramento State
Corey Shanbrom Sacramento State
Matt Krauel Sacramento State
Greg Detweiler Southern Oregon
Joe Collins Southern Oregon
Kemble Yates Southern Oregon
Larry Shrewsbury Southern Oregon
Bethany Johnson Sonoma State
Elaine Newman Sonoma State
Jillian Kimzy Sonoma State
Maddalena Heisler Sonoma State
Martha Byrne Sonoma State
Nick Franceschine Sonoma State
Rick Luttmann Sonoma State
Robert Lattimer Sonoma State
Shannon Zorn Sonoma State
Terris Becker Sonoma State
Travis Hayes Sonoma State
Dmitry Shemetov UC Davis
Jordan Snyder UC Davis