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Lecture by Professor Omar Hasan Kasule Sr. for Year 1 Semester 1 PPSD Session of Wednesday 01 November 2006
1.0 SAMPLES and POPULATIONS
The word population in statistical usage is defined as a set of objects, states, or events with a common observable characteristic or attribute. The population studied may be finite or infinite. Elements are the members of the population or a sample thereof.
A sample is a representative subset of the population selected to obtain information on the population.
A Sampling plan is the whole process of selecting a sample.
Sampling starts by defining a sampling frame (list of individuals to be sampled). The sampling units are the people or objects to be sampled.
Samples are studied because of lower and easier logistics. Some populations are hypothetical and cannot be studied except by sampling.
Samples are used for estimation of population parameters, estimation of total population, and inference on populations.
The sample is selected from the study population (population of interest). The study population is definable in an exact way and is part of the target population. Conclusions from study of the sample are referred to the target population.
2.0 RANDOM (PROBABILITY) SAMPLING
In random sampling any element has the same inclusion probability. It has the advantage of producing a representative unbiased sample. All scientific work is based on random sampling.
Simple random sampling is random selection from the population used when the population is approximately homogenous. It may not be representative if a very small sample is being selected.
Stratified random sampling involves dividing the population into groups called strata and simple random sampling is carried out in each stratum. It helps balance the sample for example by gender or age.
Systematic random sampling is used if an ordered list is available such that every nth unit is included. It may not be valid if there is a regular repeat pattern for every nth unit.
Multi-stage random sampling is simple random sampling 2 or more stages. It makes it easier to sample and collect data.
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3.0 NON-SCIENTIFIC SAMPLING
Convenience or casual sampling is subjective, depends on whims, and there is no concern about objectivity.
A quota sample is subjective selection of a pre-fixed number from each category.
Non-scientific samples are not reliable
4.0 OTHER TYPES OF SAMPLING
Cluster sampling uses clusters (groups of individuals) as sampling units instead of individuals. It is less precise than simple random sampling but is logistically easier.
Epidemiological samples involve random sampling of human populations. There are basically three types of epidemiological sampling schemes: cross-sectional, case control, and follow-up (or cohort).
Environmental sampling, static or continuous, uses direct measurements and has the advantages of being objective, individualized, quantitative, specific, and sensitive.