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.** **

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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.** **

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Non-scientific samples are not reliable

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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.