Standard syllabus
Sampling methods · Undergraduate · Math
Learning objectives from the Sampling methods syllabus, grouped by unit. Click an objective for study materials.
Topics typically covered
Click a topic for the full text and related unit practice.
Undergraduate Sampling methods — outline derived from course README sections and typical US statistics syllabi (OpenIntro / standard OER where applicable).
Sampling concepts
- Target population and sampling frame — Target population and sampling frame
- Sampling units — Sampling units
- Simple random sampling: estimates — Simple random sampling: estimates
- Variance — Variance
- Stratified sampling: optimal allocation — Stratified sampling: optimal allocation
- Systematic sampling — Systematic sampling
- Cluster and multistage sampling — Cluster and multistage sampling
Estimation and inference
- Ratio and regression estimators — Ratio and regression estimators
- Design-based vs model-based inference — Design-based vs model-based inference
- Confidence intervals for finite populations — Confidence intervals for finite populations
- Sample size determination for surveys — Sample size determination for surveys
- Two-stage sampling variance formulas — Two-stage sampling variance formulas
Nonresponse and weighting
- Unit and item nonresponse — Unit and item nonresponse
- Post-stratification — Post-stratification
- Raking (introduction) — Raking (introduction)
- Calibration estimators (overview) — Calibration estimators (overview)
- Total survey error framework — Total survey error framework
Learning objectives
Click an objective for study materials.
Sampling concepts
- Target population and sampling frame — Target population and sampling frame
- Sampling units — Sampling units
- Simple random sampling: estimates — Simple random sampling: estimates
- Variance — Variance
- Stratified sampling: optimal allocation — Stratified sampling: optimal allocation
- Systematic sampling — Systematic sampling
- Cluster and multistage sampling — Cluster and multistage sampling
Estimation and inference
- Ratio and regression estimators — Ratio and regression estimators
- Design-based vs model-based inference — Design-based vs model-based inference
- Confidence intervals for finite populations — Confidence intervals for finite populations
- Sample size determination for surveys — Sample size determination for surveys
- Two-stage sampling variance formulas — Two-stage sampling variance formulas
Nonresponse and weighting
- Unit and item nonresponse — Unit and item nonresponse
- Post-stratification — Post-stratification
- Raking (introduction) — Raking (introduction)
- Calibration estimators (overview) — Calibration estimators (overview)
- Total survey error framework — Total survey error framework
Multi-Unit Problems
Course-level sets that combine skills across study units (coming soon).
Browse Multi-Unit ProblemsWhat each unit includes
Open a unit below for full materials. Typical resources:
- Study guide
- Exam Strategy
- Common Mistakes
- Worksheets
- Word problems
- Mixed Practice
- Multi-Unit Problems
- Review
- Practice test
- Answer key
Study units
Each unit includes a study guide, worksheets, review, practice test, and answer key. One unit is free; subscribe for the full class.
- Sampling concepts
Target population and sampling frame
Coming soon - Estimation and inference
Ratio and regression estimators
Coming soon - Nonresponse and weighting
Unit and item nonresponse
Coming soon
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$1,162 · Sampling methods · 18 tutoring hrs
Study guides, worksheets, reviews, practice tests, and answer keys for 1 class. 18 tutoring hours (1 hr / week · semester). Bundle discount applied vs buying separately. Pay in full via Zelle.