Sampling methods
Undergraduate · Statistics
Syllabus focus
Standard syllabus · STEM / applied
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$60.00 · 60 min · Undergraduate · Online ($60/hr)
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Topics typically covered
Standard syllabus
Sampling concepts
- Target population, frame, and sampling units
- Simple random sampling: estimates and variance
- Stratified sampling: optimal allocation
- Systematic sampling
- Cluster and multistage sampling
Estimation and inference
- Ratio and regression estimators
- Design-based vs model-based inference
- Confidence intervals for finite populations
- Sample size determination for surveys
- Two-stage sampling variance formulas
Nonresponse and weighting
- Unit and item nonresponse
- Post-stratification and raking (introduction)
- Calibration estimators (overview)
- Total survey error framework
STEM / applied
Applied survey practice
- Analyzing complex survey data with survey package (R)
- Design effects and effective sample size
- Weighting in ACS, NHIS, or similar public surveys
- Questionnaire design and pretesting
- Ethical and legal considerations in survey research
- Reporting margins of error for media and policy audiences
Additional applied practice
- Reviewing assumptions with domain experts
- Documenting analysis choices for reproducibility
- Sensitivity analyses for key modeling decisions
- Connecting results to the original research or business question
Notes
Covers designs used by government surveys and market research. Applied sections include weighting and nonresponse adjustments used in practice.