STAT 104: Introduction to Quantitative Methods for Economics

Tentative syllabus and course calendar can be found under Files.

Course goals:

Stat 104 is an introduction to statistical methods used in economics and the social sciences.   The course will emphasize elementary probability theory, basic concepts of statistical inference, linear regression modeling, and other fundamental data analysis techniques.  The course will emphasize three main pillars of modern statistics: description, prediction, and causality.

The course will motivate statistical methods through data analysis and visualization as well as focus on the probabilistic underpinnings. Stat 104 is designed for students who intend to concentrate in a discipline from the social sciences and economics.  Stat 104 does not have any official mathematical, statistical, or computer science pre-requisites.  The course does expect students to be well-versed in mathematical notation (like sigma notation for sums), have a familiarity with computers, and be motivated to learn!

Topics covered include exploratory data analysis (descriptive statistics and basic visualizations), basic probability theory, random variables and probability distributions, basic estimation theory, statistical inference (confidence intervals and hypothesis tests), causal inference, and linear regression (simple and multiple).

Course format:

Lecture will meet twice per week. Weekly sections are optional but highly recommended.  The sections will be mostly geared towards translating from material presented in lecture to answering questions on the problem sets.

Typical enrollees:

This course is a first-course in applied statistics.  This course is primarily designed for Social Science, Economics, and future Statistics concentrators that are comfortable with a little mathematical notation and algebraic manipulation (at the Math MA/MB level).

When is course typically offered?

Stat 104 will be offered Fall only in 2024-25.

What can students expect from you as an instructor?

The course is a half-flipped classroom: roughly 2/3 of each class will be covering new material via lecture notes and the remaining 1/3 of each class will go over practice problems.  Questions from students are highly encouraged!

Assignments and grading:

There will be ~10 weekly problem sets (40% of final course grade), two in-class, timed midterms (30% of final course grade combined), and one take-home final exam with an oral/interview component (30% of final course grade combined).

Enrollment cap, selection process, notification:

There is no restriction on enrollment.  Everyone is welcome!  Note: there is an anti-req of Stat 139.

Past syllabus:

Tentative syllabus and course calendar can be found under Files.

Absence and late work policies:

Attendance is not required.  However, the best way to be successful in Stat 104 is to attend and engage in lecture and section regularly.  Students are allowed to turn-in 4 separate problem sets up to 24-hours late.