Understanding Course Workload Expectations

All course offerings are taught at the graduate level and follow an accelerated pace. You should keep this in mind when making your course selection to ensure you are allowing enough time for each class requirement.

The Health and Retirement Workshops (in the Summer and Winter) may involve a lower time commitment.

Choosing the Right Courses

Participants new to survey research or with little statistical background find Introduction to Survey Methodology an appropriate course to begin with in their studies. This is the most basic starter course the Summer Institute offers. 

In addition to this introduction course on Survey Methodology, the Summer Institute offers courses on Data Introduction, Data Collection (qualitative, quantitative, and mixed methods), Data Analysis, Sampling, and Responsive Survey Design. Most of the courses offered through the Summer Institute are taught in a supportive, virtual format designed for learners at every level. Please view the 2026 course schedule for when these current courses are offered.

Data Introduction

• Introduction to the Health and Retirement Study (HRS) Workshop: introduction to HRS that will enable course participates to get started using the data for research.

Data Collection Methods: Qualitative

• Introduction to Qualitative Research Methods: introduces qualitative research and core data collection methods.
• Qualitative Methods: Overview and Semi-Structured Interviewing: introduces semi-structured interviewing as a qualitative method, covering its goals, design, strengths, limitations, and practical techniques for conducting effective in-depth interviews.
• Data Collection Using Wearables, Sensors, and Apps in the Social, Behavioral, and Health Sciences: explores how wearables, sensors, and mobile apps can be integrated into surveys to collect high-quality, real-time behavioral and health data while addressing data quality, cost, and privacy concerns.

Data Collection Methods: Quantitative

• Designing and Writing Questions For Surveys: Guidelines and Recommendations: distills research about survey questions to principles that can be applied to write survey questions that are clear and obtain reliable answers. Provides participants with tools to use in diagnosing problems in survey questions and in writing their own survey questions.

Data Collection Methods: Mixed-Methods

• Integrating Qualitative Methods into Survey Research: introduces integrating qualitative methods into quantitative studies, showing how mixed-methods designs can strengthen research questions, execution, and interpretation.

Data Analysis, Sampling, and Responsive Survey Design

• Natural Language Processing with R: learn how to analyze and extract meaning from text data
• Sampling in Practice: designed for applied practitioners who want to master real-world sampling techniques through active learning and practical programming.
• Basic Concepts in Responsive Survey Design: introduces the core ideas of Responsive Survey Design, showing how paradata and targeted interventions can be used to improve survey effectiveness across all major survey modes.
• Interventions in a Responsive Survey Design Framework: explore how to implement and experimentally evaluate Responsive Survey Design interventions, with a focus on practical strategies for both interviewer-mediated and self-administered surveys.