Courses for PPA Majors

The BS in Public Policy and Analysis is a joint major that provides the rigor of a B.S. degree with an emphasis on topics in public policy. A combination of 17 courses, totaling 51+ credit hours, is required to complete the major. Majors will take a minimum of 9 quantitative/statistics courses offered by QTM (including three elective courses), four courses offered by Political Science, one course offered by Economics, and an additional three elective courses. Elective courses include courses from Economics, Sociology, Political Science, and Environmental Sciences and are updated / listed on our webpage each semester.

Please note, students must meet the minimum GPA requirement of 2.0 to graduate with any major or minor from the department.

All classes counting toward the degree must be taken for a letter grade.

QTM 110: Introduction to Scientific Methods

This course is designed to introduce students to the style of analytic thinking required for research in the sciences and the concepts and procedures used in the conduct of empirical research. In short, this course teaches a set of skills that are essential for both understanding the research you will encounter in substantive classes, and being able to produce high-quality original research of your own. Beyond simply learning how to be a more critical participant in the academic research community, you will also be better-prepared for career opportunities using statistical tools and the products thereof.

Students will be introduced to the basic toolkit of researchers which includes sampling, hypothesis testing, Bayesian inference, regression, experiments, instrumental variables, differences in differences, and regression discontinuity. More importantly, students will learn the principles of critical thinking essential for careful and credible research.

Prerequisites: None

GER: None

Credits: 3

Offering schedule: Fall, SP18

NOTE: This course is not QTM 100, nor is it a sequence course related to QTM 100. QTM 100 is a basic statistics course unrelated to the QSS major.

QTM 120: Math for Quantitative Sciences

This course is a mandatory course for all Quantitative Sciences majors. It is also a prerequisite for the more advanced course offerings in the major including Regression Analysis, Maximum Likelihood Estimation, Longitudinal Data Analysis as well as the game theory sequence. The goal of the course is to provide the necessary mathematical background for students to properly derive and implement common statistical modeling techniques employed in the sciences. 

In the first half of the course we will cover core concepts in linear algebra. The second half of the course focuses on multivariable calculus. This course focuses on the computation skills necessary for quantitative research.

Prerequisites: Calculus I or equivalent

GER: MQR

Credits: 4

Offering schedule: Fall and Spring

QTM 150: Statistical Computing I

This course provides an introduction to statistical computational tools for analyzing data. The material is selected to enable you to become proficient enough to actively implement the methods and tools in your scientific research. This will require you to practice the material outside of class.

By the end of the course, students should be able to 1) deal with complex and messy real data, 2) use graphics to explore and understand data, 3) gain familiarity with basic data collections, storage, and manipulation, and 4) fluently reshape data into the most convenient form for analysis or reporting. 

Prerequisites: None

GER: None

Credits: 1

Offering schedule: Fall, SP18

QTM 151: Statistical Computing II

This course provides a practicum of skills for data science and an introduction to how to do data science with R.  The material is selected to enable you to get data into the most useful structure, transform it, visualize it, and model it. This will require you to practice the material outside of class.

By the end of the course, students should be able to (1) deal with complex and messy real data (2) use graphics to explore and understand data (3) gain familiarity with basic data manipulation, (4) fluently reshape data into the most convenient form for analysis, and (5) automate cleaning and analysis.

Prerequisites: QTM 150

GER: None

Credits: 1

Offering schedule: Spring

QTM 210: Probability & Statistics

This course covers the structure of probability theory, which is the foundation of statistics, and provides many examples of the use of probabilistic reasoning. It discusses the most commonly encountered probability distributions, both discrete and continuous. The course considers random sampling from a population, and the distributions of some sample statistics. It deals with the problem of estimation: the process of using data to learn about the value of unknown parameters of a model. Finally, it discusses hypothesis testing: the use of data to confirm or reject hypotheses formed about the relationship among variables. 

Prerequisites: QTM 120

GER: MQR

Credits: 4

Offering schedule: Fall and Spring

QTM 220: Regression Analysis

This course covers basic techniques in quantitative research. It introduces students to widely used procedures for regression analysis for descriptive and causal inference, and provides intuitive, applied, and formal foundations for regression and more advanced methods treated later in the major course sequence.  The first half of the course addresses the foundations of statistical hypothesis testing via linear regression models. This module of the course will provide the formal derivation of the ordinary least squares regression model as well as an overview of its practical implementation and the underlying modeling assumptions. The second module shifts focus to the implications of violating the assumptions of the OLS model including issues of omitted variable bias, multicollinearity, and heteroskedasticity. While the course will emphasize the mathematical foundations of these concepts, each topic will also cover the implementation of the relevant methods in the statistical computing program R. 

Prerequisites: QTM 120, QTM 210

GER: MQR

Credits: 4

Offering schedule: Fall, SP18

POLS 100: National Politics in the United States

Origins, principles, structures, processes, and practices of American national government. Stresses different perspectives on democratic theory and practice, and the adequacy of governmental institutions.

Prerequisites: None

GER: HSC

Credits: 3

Offering schedule:

POLS 200: Intermediate National Politics of the U.S.

This intermediate course in American politics examines how the public, elected officials and political institutions interact to govern and make public policy.

Prerequisites: None

GER: None

Credits: 3

Offering schedule:

POLS 360: Public Policy Process

How national public policies develop. Focus on who American governing actors and elites are, what they control, how they work together, and how issues thereby develop, recur, and evolve into policy.

Prerequisites: None

GER: HSC

Credits: 3

Cross-listed: SOC 377

Offering schedule:

POLS 369: Policy Analysis

Overview of the quantitative and qualitative methodologies employed by analysts in determining whether public programs and policies work. Attention is also given to research utilization and the role of analysis in the policymaking process.

Prerequisites: None

GER: HSC

Credits: 3

Offering schedule:

ECON 101: Principles of Microeconomics

Introduction to the theory of markets, including consumer and producer choice and how they interact to determine prices and resource allocations. Applications include price controls, production, market structures, environmental economics, governmental regulation of the economy, labor and capital markets, and international exchange.

Prerequisites: None

GER: HSC

Credits: 3

Offering schedule:

PPA Electives

QTM Elective Courses (3 required)

QTM electives include 300- and 400-level lecture and seminar style classes (excluding QTM 390, QTM 398R, QTM 496, and QTM 497). Check out the Course Catalog for an inclusive list.

Policy Elective Courses (3 required)

Check out the approved policy elective list, which is an exhaustive list of courses approved as policy electives in the PPA major.

Looking for elective offerings by semester? See here:

Fall 2017 Policy Elective Courses

Spring 2018 Policy Elective Courses