LBJ Survey Design and Analysis
  • Syllabus
  • Schedule
  • Readings
  • Assignments
  • Univision Project
  • Labs

On this page

  • Course information
  • One course, two connected tracks
  • Course overview
  • Learning objectives
  • Course structure
  • Assessment
    • Preparation and professional participation
    • R and statistics labs
    • Individual methods assignments
    • Univision project milestones
    • Individual poll analysis memo
    • Coauthored report and presentation
    • Individual reflection and contribution statement
  • Course materials and software
  • Communication and submission
  • Use of artificial intelligence
  • Professional and ethical responsibilities

Survey Design and Analysis

PA 397C · Fall 2026

LBJ School of Public Affairs · Fall 2026

Survey Design and Analysis

Learn the complete lifecycle of professional survey research while helping design, execute, analyze, and communicate a live 2026 public-opinion poll with Univision News.

Mondays · 9:00 a.m.–12:00 p.m. SRH 3.214 Sergio I. García-Ríos

Schedule Thirteen sessions from research design through the final briefing. Assignments Individual methods work, project milestones, and the final report. R & Statistics Labs Guided coding workshops with shorter independent applications. Univision Project The live polling partnership at the center of the semester.

Course information

Instructor Sergio I. García-Ríos
Meeting Mondays, 9:00 a.m.–12:00 p.m.
Location SRH 3.214
Office hours By appointment
Teaching assistant To be announced
Course partners Univision News and an additional UT unit to be announced

One course, two connected tracks

1

Survey design and production

Move from research objectives and measurement through sampling, questionnaire testing, fieldwork, quality assurance, weighting, and public release.

2

R programming and statistical analysis

Build a reproducible workflow for cleaning survey data, describing responses, quantifying uncertainty, estimating models, and communicating results.

Course overview

This course teaches students how to design, execute, evaluate, analyze, and communicate rigorous survey research. Rather than treating survey methodology as a collection of isolated techniques, we will organize the semester around the complete lifecycle of a major public-opinion poll.

The central applied experience will be a live partnership with Univision News. Students will participate in the stages of developing and executing a 2026 public-opinion poll, from defining research objectives and writing questions through quality assurance, analysis, and public communication. An additional University of Texas partner may join the collaboration.

The partnership gives students access to the practical decisions, compromises, deadlines, and ethical responsibilities that shape professional survey research. Because this is a real polling project, some dates and deliverables may change as fieldwork and partner needs evolve.

Learning objectives

By the end of the semester, students will be able to:

  1. Translate substantive and policy questions into a feasible survey research design.
  2. Evaluate probability and nonprobability samples using the total survey error framework.
  3. Write, revise, translate, and test survey questions that measure concepts reliably and validly.
  4. Assess tradeoffs among survey modes, sampling frames, recruitment strategies, and fieldwork protocols.
  5. Develop a questionnaire, survey flow, and quality-assurance plan suitable for professional fielding.
  6. Diagnose coverage, nonresponse, measurement, and data-quality problems.
  7. Clean, document, weight, analyze, and visualize survey data reproducibly in R.
  8. Quantify and communicate uncertainty without overstating what a poll can establish.
  9. Produce accessible, ethical, and decision-relevant survey findings for academic, policy, and public audiences.
  10. Collaborate effectively on a time-sensitive research project with external partners.

Course structure

The survey-production track follows this cycle:

  1. Purpose and design: research objectives, stakeholders, ethics, and total survey error.
  2. Measurement: concepts, question wording, response options, order effects, translation, and testing.
  3. Representation: target populations, frames, sampling, modes, recruitment, nonresponse, and weighting.
  4. Production: questionnaire integration, programming, quality assurance, fieldwork, and documentation.
  5. Analysis and communication: cleaning, uncertainty, subgroup analysis, visualization, reporting, and release.

Class meetings will combine discussion, methodological workshops, R labs, project meetings, and production sprints. The schedule identifies the planned focus for each Monday.

Assessment

Component Weight
Preparation and professional participation 10%
R and statistics labs 25%
Individual methods assignments 15%
Univision project milestones 15%
Individual poll analysis memo 10%
Coauthored LBJ/Univision report and presentation 20%
Individual reflection and contribution statement 5%
Total 100%

Preparation and professional participation

Participation includes arriving prepared, contributing constructively, giving useful feedback, meeting production deadlines, documenting decisions, and supporting the work of the project team. Attendance matters because many workshops and partner activities cannot be recreated individually.

R and statistics labs

Five substantial labs teach R programming and the statistical foundations of survey analysis. Most of each lab is completed together during class through guided coding, interpretation, and troubleshooting. Students then complete a shorter “On Your Own” application individually. Topics include data wrangling, descriptive statistics, visualization, sampling and inference, survey weights, regression, predicted probabilities, and reproducible reporting.

Individual methods assignments

Three short assignments require students to evaluate a published poll, diagnose and improve survey measurement, and defend a sampling and mode recommendation. These assignments ensure that each student develops independent methodological judgment.

Univision project milestones

Teams will complete staged products such as a project charter, measurement module, cognitive-testing report, representation plan, instrument quality-assurance review, and analysis plan. Milestones are working documents that feed directly into the live poll and final report.

Individual poll analysis memo

Each student will independently analyze a substantive question using the poll data. The memo must include reproducible R code, appropriate use of weights and uncertainty, at least one effective visualization, and a concise interpretation written for a policy or public audience.

Coauthored report and presentation

The class will produce one coherent report using data from the poll. Teams will take primary responsibility for different substantive sections while reviewing and revising the full document. The report will be designed for a public and policy audience and, subject to partner approval, carry LBJ and partner branding.

Individual reflection and contribution statement

Each student will document their contributions, explain important methodological decisions, evaluate the collaboration, and identify what they would change in a future survey project.

Course materials and software

There is no single textbook that covers the full course. Required readings will combine foundational survey-methodology research, recent methodological reports, applied examples, and documentation. Readings will be posted on the schedule and Canvas.

We will use R and RStudio or Posit Cloud for analysis and Quarto for reproducible documents. No prior mastery of R is required, but students are expected to practice consistently and seek help early.

Communication and submission

The course website is the public home for the syllabus, schedule, assignments, and labs. Canvas will be used for protected readings, grades, and assignment submission. The teaching team will explain the channel used for project communication during the first class.

Unless an assignment says otherwise, reproducible work should include both the source file and the rendered output.

Use of artificial intelligence

Generative AI can support brainstorming, coding, editing, and troubleshooting, but it cannot substitute for methodological judgment or individual learning. Students must follow the instructions for each assignment, verify all AI-assisted work, protect confidential or embargoed project information, and disclose substantive AI assistance. No restricted survey instrument, respondent data, partner communication, or unpublished result may be entered into a public AI system without explicit authorization.

Professional and ethical responsibilities

This course may involve embargoed instruments, partner discussions, and unpublished results. Students must follow all confidentiality, data-security, attribution, and release rules established for the project. Participation in a course does not authorize independent public release of project materials or findings.

Course policies on accommodations, academic integrity, safety, religious observances, names and pronouns, and university resources will be aligned with current University and LBJ guidance and posted before the semester begins.

PA 397C · Fall 2026 · LBJ School of Public Affairs

 

Course materials licensed CC BY 4.0 unless otherwise noted.