Learning to Make Better Decisions at NYU: Saturday Syllabi

Last week the Saturday Syllabi was all about the summertime, but we’re going to have to bring the dogs days back to reality. As all the lucky undergrads and grads out there head back to school in the next week or two to start up classes and get their actual syllabi, it’ll be tough to choose which ones to keep and which ones to drop. If the prospect of taking yet another bio class that you don’t need or having to take that boring psych class at 7 a.m. is keeping you up at night, you’re in luck! That is, if you’re willing to read another syllabus.

This week we’ll take a look at a core curriculum class at NYU that’s all about learning to make good decisions. Hopefully by the end of reading it you’ll think you made the right choice.

Class: Probability, Statistics, and Decision Making, an undergraduate course part of the school’s core curriculum.

Professor: Alexander L. Hanhart

Prerequisites: “This course assumes that the student has completed two years worth of high school algebra. Specific technical skills include basic arithmetic, solving for unknown quantities, inequalities, factoring, standard simplification techniques, etc. Students will be reminded of such skills as they are needed in lecture.”

Textbook: For All Practical Purposes, 8th edition

Course Description: “The topics are the following: Data representation and characteristics. Finding relationships between data sets. Sampling, experiments, and confidence. Probability. Fair division and apportionment. Elementary game theory. In all cases we will pay special attention to the application of these topics to the decision making process and how we can use mathematics to quantify the notion of the “best” decision. The specific topics mentioned correspond roughly to chapters 5-8 and 13-15 in the text.”

Homework: “Proficiency at mathematics is divided into two parts: (1) an understanding of logic, rigor, and argument; and (2) skill in applying this understanding. As with any skill, practice is required for mastery! In general this practice takes the form of Homework assignments, which will be announced regularly in class and made available online with due dates.”

Exams: “There will be one hour long midterm exam worth 30% of the final grade. There will also be a cumulative final exam worth 40%. The exams will consist mostly of computational questions, with a few reasoning exercises requiring a short response. Mostly correct answers with supporting work will receive partial credit. The exams may involve multiple choice and/or true and false questions. In such cases, no partial credit is allowed.”

A class specifically about decision-making seems fairly mysterious. I can’t imagine the feeling poor NYU undergrads must have coming out of the other end of the class and thinking they don’t have a better grasp on the concept. It must be one of the saddest college realizations ever.

But the enigma of the class may be because a lot of its shading is from the book that we don’t have access to. Still, the general subject matter is enough to arouse any inquisitive mind even if they hate math, which, let’s face it, is a lot of us. When you get down to it, the ability to discern a conclusion in a quantitative way in the face of something that seems instinctual at a basic level is an intriguing possibility. It sounds a bit robotic if you ask me, but interesting enough to take the plunge, do some algebra, and figure out if you can get a leg up on making the right decisions in your life.

The only gripe is that there aren’t more materials to cull from, leaving us wanting more. But this might be the type of class that comes alive during the collaborations and in-class environment. On the other hand, it could be a terribly boring class that has a catchy title to pull in unsuspecting suckers just because it sounds interesting.

How can we use math to determine decision making anyway? We just have to take this class and get the numbers to find out. But maybe we’re better off just leaving inclinations like that to psych class.