This is an undergraduate level course on design and analysis of sample surveys.
This course unit is designed with the intention to enable students apply principles of survey sampling and to understand and apply the different methods used in sampling.
Learning Outcomes: By the end of this course the student should be able to:
- Define a sample survey, and identify the advantages and principal steps in organizing a survey.
- Describe the probability and purposive types of samples.
- Apply simple random sampling both in proportions and percentages.
- Describe the principles of estimating sample size. Discuss the methods of random sampling such as stratified, systematic, cluster, multistage and proportional.
- Determine the ratio and regression estimators.
- Distinguish between sampling and non-sampling errors.
- Outline how national surveys are conducted, and the work done by the Kenya National Bureau of Statistics.
Course Description: Sample survey: definition, advantages and principal steps in organizing a survey. Types of samples: probability and purposive. Simple random sampling: sampling proportions and percentages; estimating sample size; stratified random, systematic, cluster and multistage samples; selections with p.p.s (probability proportional to size). Ratio and regression estimators, sampling and non-sampling errors, organisation of national surveys, and the Kenya National Bureau of Statistics. Use of computer packages.