Course Details in 2025/26 Session

Module Title	LH Sampling Techniques
School	Mathematics
Department	Mathematics
Module Code	06 31301
Module Lead	Yin Jing
Level	Honours Level
Credits	10
Semester	Semester 2
Pre-requisites
Co-requisites
Restrictions	Available only to students on the JI dual degree pro-grammes
Exclusions
Description	Sampling technique is a particular branch of statistics mainly concerned with extracting a representative sample from surveys, then estimating the unknown parameters of the population. This module provides some commonly used sampling de-sign methods, such as simple random sampling, stratified sampling, cluster sampling, systematic sampling, and mul-tistage sampling. This module teaches estimation methods such as simple estimation, ratio estimation, and regression estimation methods. The module emphasises practicality and applicability. Stu-dents are guided to use theory appropriately for practical survey design, and build sampling schemes based of actual surveys and auxiliary information design.
Learning Outcomes	By the end of the module students should be able to: Understand the theoretical principles of sampling. Understand the relationship between sampling schemes for survey design. Design a sampling scheme for a practical survey. Use sampling design methods, such as simple random sampling, stratified sampling, cluster sampling, systematic sampling, and multistage sampling. Apply methods estimation appropriate to the chosen sampling scheme
Assessment
Assessment Methods & Exceptions	Assesment: Assignments (30%) Final Exam (70%): a 2 hour examination Re-assessment (where allowed): a 2-hour resit examination (100%)
Other
Reading List