This is a list of all courses offered by the Math Department.  Not all courses are offered each year.  What is provided is a general description of the courses and the prerequisites.  The actual content may vary.

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Description

Simple random sampling. Sampling for proportions. Estimation of sample size. Sampling with varying probabilities. Sampling: stratified, systematic, cluster, double, sequential, incomplete. Also listed as SURV 440.

Prerequisites

1 course with a minimum grade of C- from (STAT401, STAT420)


Level of Rigor

Standard


Sample Textbooks

Sampling, by Thompson

Sampling: Design and Analysis, by S. L. Lohr


Applications



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Additional Notes

Duplicate credit with Surv440

Students interested in grad school in STAT should consider this course

Topics

Basic concepts

Populations, samples, sampling frames.

Sampling design, statistics, bias.

Sampling and nonsampling errors.

(0.5 week)

Simple Random Sampling

Estimates of population mean, total, proportion and variance and their sampling properties.

Confidence limits, use of normal approximation.

Auxiliary information, ratio and regression estimators.

(4.5 weeks)

Stratified Samples

Definitions, weighting and estimators.

Optimal allocation, poststratification.

(2 weeks)

Unbiased Estimation for Cluster and Two-Stage Sampling

Single-stage, two-stage, and multi-stage cluster sampling.

Fixed and random clusters.

With-replacement and without-replacement sampling of PSU's.

Approximate variance estimators.

(4 weeks)

Advanced Topics

Variance estimation, categorical data analysis, regression in complex surveys.