Sampling Survey

Course No.: SMI1121001     Credit(s):2

Course Description

The objectives of this course are to teach basic ideas of sampling from an applied perspective. The course will cover the main techniques used in actual sampling practice — simple random sampling, stratification sampling, systematic sampling, cluster sampling, multistage sampling, and probability proportional to size sampling. The course will also cover sampling frames, cost models, sampling error estimation techniques, non-sampling errors, and computation for missing data.

Course Learning Outcomes

The student learning outcomes are what student would be able to know and to do on the completion of this course. In details are:

lTo understand the basic designs for selecting samples for applied survey research.

lTo design and implement surveys with the following sampling designs: simple random, systematic, stratified, cluster and multistage.

lTo develop problem-solving skills in designing survey sample plans.

Relationship to Other Courses

Pre-requisites: Statistics, Probability Theory

Textbook and Reading Lists

Textbook:

Yongjin Jin, Sampling Survey (3rd edition). China Renmin University Press, 2012.

Suggested reading lists:

Shiyong Feng, Jiaxun Ni, Guo Zou, Theory and Methods of Sampling Survey (2nd edition). China Statistics Press, 2012.

Kish, Leslie, Survey Sampling. New York: Wiley, 1965.

William G. Cochran, Sampling Techniques (3rd edition). Wiley,1977,

Course Assessment

Course Schedule