Module Identifier MX37510 Module Title THEORY AND PRACTICE OF SAMPLING Academic Year 2001/2002 Co-ordinator Mr David Jones Semester Semester 2 Other staff Ms Sylvia Lutkins Pre-Requisite MX36510 Mutually Exclusive MA27510 Course delivery Lecture 15 x 1 hour lectures. Practical 4 x 2 hour practical classes. Seminars / Tutorials 3 x 1 hour group discussions. Assessment Survey report 60% Course work 40% Resit assessment 2 Hours practical examination, during which candidates may consult their notes (50%); survey report (50%).

General description

This module combines the theory of sampling with the experience of planning and conducting a sample survey.

Aims

This module will give the student an appreciation of the value of statistical theory together with the difficulties involved in the practical application of these ideas. The student will gain experience in working as part of a team, planning and organising a sample survey, producing a questionnaire, handling and analysing real data and writing a report.

Learning outcomes

On completion of this module, a student should be able to:
• implement the theory of finite sampling;
• calculate sample sizes necessary to achieve predefined goals;
• draw samples of appropriate kinds from various populations;
• compile a questionnaire to obtain quality information;
• collect, collate, present, analyse and interpret the data from a sample survey.

Syllabus

1. INTRODUCTION: The benefits of sampling. The need for thorough planning. Populations, sampling units, sampling frames, sampling schemes. The art of asking the right question to obtain quality information.
2. FINITE SAMPLING THEORY: Theory of simple random sampling. Finite population corrections. Stratification, Quota, Cluster, Systematic and Multi-stage methods. Comparison of sampling designs for estimating means, totals, variances, proportions. Optimal sampling when total size or total cost is fixed.
3. PLANNING A SAMPLE SURVEY: Defining the problem, setting a time-schedule, deciding upon a suitable sampling scheme, compiling a questionnaire.
4. SOME PROBLEM AREAS: Target populations. Non-response. Surveying sensitive issues. Wildlife populations, elusive populations. Post-stratification.
5. DATA ANALYSIS: Checking for errors. Analysis of contingency tables, comparing proportions, lucid presentation of results.