Fall 2026 Schedule

The schedule follows the official UT Austin Fall 2026 calendar and the anticipated Univision polling cycle. Because this is a live project, milestone dates may shift. Changes will be announced in class and posted here.

At a glance

Session	Date	Survey-production focus	R/statistics lab or principal product
1	Aug. 24	Why polls fail and what good survey design requires	Initial Survey Autopsy diagnostic; R/Quarto setup
2	Aug. 31	Research objectives, ethics, and total survey error	Lab 1: R workflow and survey data
—	Sept. 7	Labor Day—no class
3	Sept. 14	Concepts, measurement, and questionnaire architecture	Construct map
4	Sept. 21	Question wording, response options, order, and sensitive questions	Draft question module
5	Sept. 28	Cognitive interviewing, multilingual equivalence, and revision	Lab 2: Descriptives, measures, and visualization
6	Oct. 5	Target populations, frames, probability and nonprobability samples	Sampling assessment
7	Oct. 12	Modes, recruitment, coverage, nonresponse, and inference	Lab 3: Sampling, uncertainty, and comparisons
8	Oct. 19	Questionnaire integration, programming, randomization, and QA	Programmed instrument and QA log
9	Oct. 26	Fieldwork, paradata, fraud, respondent quality, and documentation	Fieldwork dashboard plan
10	Nov. 2	Cleaning, coding, missing data, weights, and design effects	Lab 4: Weighted survey estimates
11	Nov. 9	Estimation, uncertainty, subgroup comparisons, and modeling	Analysis plan and production sprint
12	Nov. 16	Modeling, visualization, interpretation, and communication	Lab 5: Regression and reproducible reporting
—	Nov. 23	Fall break—no class
13	Nov. 30	Report production, peer review, and partner briefing rehearsal	Full report draft
14	Dec. 7	Final presentations, project retrospective, and handoff	Final report and presentation

Detailed schedule

Session 1 · August 24

Why polls fail—and what good survey design requires

We begin with the Initial Survey Autopsy diagnostic, completed before formal instruction in survey methodology. Students work backward from a published report’s claims to the design information provided—or omitted. The goal is to establish a shared language for evaluating survey evidence and introduce the semester partnership.

Session 2 · August 31

Research objectives, stakeholders, ethics, and total survey error

We translate stakeholder questions into researchable objectives, identify the target population and intended claims, and use total survey error to anticipate threats before writing questions.

Lab 1 begins in class: RStudio projects, Quarto, importing survey data, reading a codebook, missing values, recoding, summarizing, and reproducible workflow.

September 7

Labor Day—no class

Session 3 · September 14

Concepts, measurement, and questionnaire architecture

We move from abstract concepts to indicators, distinguish measurement from operational convenience, and design the overall flow of a questionnaire.

Session 4 · September 21

Question wording and response design

We examine comprehension, retrieval, judgment, response mapping, acquiescence, social desirability, question order, response scales, and treatment of uncertainty.

Session 5 · September 28

Testing and multilingual equivalence

Students conduct and evaluate cognitive interviews, identify systematic problems, and revise modules. We address translation, cultural adaptation, and equivalence across English and Spanish instruments.

Lab 2 begins in class: distributions, proportions, cross-tabulations, grouped summaries, measurement, scales, and accurate visualization with ggplot2.

Session 6 · October 5

Sampling and representation

We define the inferential population, compare sampling frames and recruitment sources, and assess probability and nonprobability approaches.

Session 7 · October 12

Modes, recruitment, and nonresponse

We analyze mode effects, coverage, contact strategies, incentives, accessibility, response rates, and nonresponse bias.

Lab 3 begins in class: simulation, sampling distributions, standard errors, margins of error, confidence intervals, hypothesis tests, and subgroup comparisons.

Individual Assignment 1: Poll Autopsy assigned. Due Sunday, October 18, by 11:59 p.m.

Session 8 · October 19

Programming and quality assurance

The class integrates modules, reviews logic and randomization, tests mobile and bilingual displays, and maintains a formal issue log.

Session 9 · October 26

Fieldwork and data quality

We establish fieldwork monitoring rules, examine paradata and fraud indicators, and distinguish defensible quality controls from post hoc deletion of inconvenient respondents.

Session 10 · November 2

Cleaning, coding, and weighting

Students develop a reproducible workflow for labels, missingness, derived variables, open-ended coding, weighting, effective sample size, and documentation.

Lab 4 begins in class: the R survey package, weighted and unweighted estimates, design effects, effective sample size, and defensible toplines.

Session 11 · November 9

Analysis and uncertainty

We estimate toplines, compare subgroups, quantify uncertainty, account for weights and design effects, and avoid common errors in interpreting close differences.

Session 12 · November 16

Visualization and public interpretation

Students turn results into accurate, accessible graphics and write claims that match the strength of the design and evidence.

Lab 5 begins in class: introductory linear and logistic regression, categorical predictors, interactions, predicted probabilities, model-based graphics, and reproducible Quarto reporting.

November 23

Fall break—no class

Session 13 · November 30

Report production and briefing rehearsal

Teams integrate the substantive narrative, methods statement, tables, graphics, limitations, and partner feedback into a coherent report.

Session 14 · December 7

Final presentation and project retrospective

The class presents the final work, evaluates the production process, documents remaining decisions, and completes the project handoff.