Design of finite population sample surveys. Stratified, systematic, and multistage cluster sampling designs. Sampling with probability proportional to size. Auxiliary variables, ratio and regression estimators, non-response bias.
Additional Requirements for Graduate Students: Additional and/or alternative problems of a more challenging
nature will be required for graduate students on homework and
exams.
Athena Title
Sampling and Survey Methods
Prerequisite
STAT 4230/6230 or permission of department
Semester Course Offered
Offered fall
Grading System
A - F (Traditional)
Student Learning Outcomes
Students will learn different probability-based methods for sampling from a finite population.
Students will learn strengths and weaknesses of these methods, enabling them to assess which method is preferable for a particular problem.
Students will learn inference methods for population means, population totals, and population proportions, which are discussed for each of the sampling methods.
Students will learn about the possible use of ratio estimators, regression estimators, and difference estimators in the presence of auxiliary information.
Students will learn expressions for estimated variances of estimators and bounds for the error of estimation and will also learn how to use these quantities in drawing and formulating conclusions about the population parameters of interest.
Students will learn how to select an appropriate sample size for each objective and for every sampling method discussed.
Students will learn how to perform inferences based on the methods in this course by using a statistical software package.
Topical Outline
Different plans for probability sampling from a finite population
