Course Syllabus
Please note that this is an abbreviated version of the full 2019 syllabus; please click here to see the full course syllabus. Selected elements from the syllabus can be found below:
CLASS MEETINGS
9:00-11:30 AM, Wednesdays, January 9 - April 24, 2019
Room 1208 Lefrak, University of Maryland; Room G300 ISR-Perry, University of Michigan
INSTRUCTORS
Brady T. West, Room 4118 ISR (Michigan) & Room 1218 Lefrak (Maryland)
734/223-9793 (cell); 734/647-4615 (office);
Email: bwest@umich.edu
Office hours by appointment
Yajuan Si, Room 4014 ISR (Michigan) & Room 1218 Lefrak (Maryland)
845/798-2013 (cell); 734/764-6935 (office);
Email: yajuan@umich.edu
Office hours by appointment
ADMINISTRATIVE ASSISTANT
Administrative / Technical: Jodi Holbrook, Room 4012 ISR, University of Michigan
734/764-6595; hjodi@umich.edu
COURSE CONTENT, GOALS, & EXPECTED COMPETENCIES
Applied Sampling is an applied statistical methods course concerned almost exclusively with the design of data collection. Little of the analysis of collected data will be discussed, but rather the course will concentrate on problems of applying sampling methods to human populations.
The course is presented at a moderately advanced statistical level. While mathematical aspects are not covered, statistical notation and some algebraic derivations are. A thorough understanding of statistical notation and principles will be needed.
The goal of the course is to develop sampling skills and an understanding of the principles and properties of sampling techniques used in scientific research. Students will learn and be tested on the following competencies:
- The meaning and application of variance in populations and sampling distributions, and understand the difference between element and sampling variance.
- The methods and properties of sampling techniques including simple random, stratified random, cluster, systematic, multistage, probability proportionate to size, and stratified multistage sampling.
- How sampling variance is estimated for the mean, proportions, and totals (aggregates) for each of the sampling techniques examined in the course.
- How to estimate and use in practice sampling variance for complex sample surveys, including balanced and jackknife repeated replication and the Taylor series approximation.
- The differences between sampling and non-sampling errors.
- How nonresponse can affect survey estimates and what techniques can be used to reduce nonresponse and compensate for nonresponse bias.
Course Summary:
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