Courses in: Analytical Methods and Evaluation

Policy Advocacy Evaluation: Designing Rigorous and Useful Evaluations

This class explores the important evaluation area of policy advocacy evaluation. As development practice shifts to focus on the structural drivers of poverty around the world, and seek long-term social and institutional change, interventions increasingly involve shaping policies, programs and social norms. This class examines the theoretical and practical challenges of measuring influence on policy deliberation and implementation. It explores emerging approaches developed to provide rigor and actionable insights about what works and what doesn’t.

Python Coding for Public Policy

This 7-week course exposes the students to the application and use of data analytics in setting public policy. The course does so by teaching introductory technical programming skills that allow students to learn and apply Python code on pertinent public policy data, while emphasizing on applicability. The course is accompanied by readings for each class in order to contextualize why data analytics supplements but doesn’t replace the student / professional role in setting public policy.

R Coding for Public Policy

R is a powerful open source language and environment for statistical computing and graphics. R provides a wide selection of statistical and graphical techniques. It is rapidly becoming the leading language in data science and statistics. R can easily tackle linear and nonlinear modelling, statistical tests, time series analysis, classification, clustering and more.

Data Visualization and Storytelling

In our increasingly data-reliant and data-saturated society, people who understand how to leverage data to generate insights have the power to change the world. Data visualization and storytelling is a crucial skill for policy and data analysts, communications and marketing professionals, and managers and decision-makers within nonprofits, social organizations and the government. With the advent of visualization tools that do not require coding, data storytelling is also an attainable skillset for people with varying levels of technical ability.

Big Data Analytics for Public Policy

The goal of the Big Data Analytics for Public Policy is to develop the key data analytics skill sets necessary to harness the wealth of newly-available data. Its design offers hands-on training in the context of real microdata. The main learning objectives are to apply new techniques to analyze social problems using and combining large quantities of heterogeneous data from a variety of different sources. It is designed for graduate students who are seeking a stronger foundation in data analytics.

Introduction to Database Design, Management, and Security

The goal of this course is to train advanced students on the principles, practices, and technologies required for good database design, management, and security. An introduction to the concepts and issues relating to data warehousing, governance, administration, security, privacy and alternative database structures will be provided. The course concentrates on building a firm foundation in information organization, storage, management, and security.

Introduction to Data Analytics for Public Policy, Administration, and Management

The goal of this course is to establish a first-principles understanding of the qualitative and quantitative techniques, tools, and processes used to wield data for effective decision-making. Its approach focuses on pragmatic, interactive learning using logical methods, basic tools, and publicly available data to practice extracting insights and building recommendations. It is designed for students with little prior statistical or mathematical training and no prior pre-exposure to statistical software.

Using Large Data Sets in Policy Research

This half-semester course will focus on the analysis of complex survey data. The focus will be on using secondary data of this type. Using Stata, we will discuss how regression analysis differs when using complex survey data as well as data-cleaning procedures, including trimming, variable transformations, and dealing with missing data. Students will produce a short memo, using real survey data, to analyze a simple research question.

Designing Data Collection for Program Evaluation, Policy, and Management

This half-semester course will include a qualitative and a quantitative component. We will begin with a discussion of using focus groups as a tool for data collection. We will spend the rest of the course talking about survey designs (including probability and non-probability sampling) and questionnaire development, as well as implementation issues. Students will produce a short focus-group proposal or survey questionnaire.

Large Scale Data Analysis I

The past decade has seen the increasing availability of very large scale data sets, arising from the rapid growth of transformative technologies such as the Internet and cellular telephones, along with the development of new and powerful computational methods to analyze such datasets. Such methods, developed in the closely related fields of machine learning, data mining, and artificial intelligence, provide a powerful set of tools for intelligent problem-solving and data-driven policy analysis.

Large Scale Data Analysis II

The past decade has seen the increasing availability of very large scale data sets, arising from the rapid growth of transformative technologies such as the Internet and cellular telephones, along with the development of new and powerful computational methods to analyze such datasets. Such methods, developed in the closely related fields of machine learning, data mining, and artificial intelligence, provide a powerful set of tools for intelligent problem-solving and data-driven policy analysis.

Behavioral Economics and Public Policy Design

Standard economic theory assumes that individuals are fully rational decision-makers; however, that is often not the case in the real world. Behavioral economics uses findings from lab and field experiments to advance existing economic models by identifying ways in which individuals are systematically irrational. This course gives an overview of key insights from behavioral science and identifies ways in which these findings have been used to advance policies on education, health, energy, taxation, and more.