Predicting Presidential Elections and Other Things
One Section Available to Choose From:
|Course Dates||Weeks||Meeting Times||Status||Instructor(s)||CRN|
|July 14, 2014 - August 01, 2014||3||M-F 3:50-6:40P||Open||Simon Freyaldenhoven||10671|
In a world where we are bombarded with predictions and opinions every day, knowledge of the tools introduced in this class will enable students to critically evaluate them. In that sense this course can be seen as an intuitive introduction to the quantitative tools used in the social sciences. Through the analysis of a wide range of topics such as those indicated below, students will gain a deeper understanding not only of those topics but also of the ways topics like these can be analyzed.
Presidential Elections, marathon times, wine quality, extramarital affairs, interest rates. What all of these topics have in common is that they can all be explained and analysed using the tools of the social sciences and statistics. At a time where information and opinions are readily available in vast amounts through the internet, being able to separate the wheat from the chaff is an important asset that will allow students to form their own informed opinion on important matters.
We will generally start by proposing a theory, then proceed to gather data, and use this data to test our theory. We will then address potential pitfalls and critically evaluate our results. Finally we will be discussing implications of and predictions from our results. In other words we will be moving from a general idea of how something works to a specific prediction of what it will be like in the future.
This course is intended not only for students with interests in the social sciences, but also those who may ultimately look to pursue a different career and nevertheless recognize the importance of the skills described above. While the introduction to some basic statistical techniques is inevitable given the nature of this class, this will be kept to a minimum and the main focus will be on its applications.
By the end of this course, students will be able to critically evaluate the quality of data analyses. They will be able to judge the conclusions and predictions drawn from the analysis of data and recognize potential pitfalls. Further, upon completion of this course, students will be able to conduct some basic data analysis themselves.
This class does not require any formal prerequisites. However, some affinity with mathematics will be helpful and/or expected.