Original paper

Probability Sampling
Probability sampling specifies to the researcher 
that each segment of a known population will be 
represented in the sample. Probability samples 
lend themselves to rigorous analysis to determine 
the likelihood and possibility of bias and error 
(2). Random selection is the process of choosing 
the components of a sample that ensures each 
member of a population stands the same chance of 
selection (3,4). The characteristics of the sample are 
assumed to be similar to the characteristics of the 
total population it is drawn from. The initial step in 
choosing a sample, therefore, is to define the sample 
frame.
Sample Frame
The sample frame represents those individuals who 
have a chance to be included among those selected 
in a sample selection procedure (4). Examples 
of sampling frames include (a) learners enrolled 
in a graduate school, (b) a city phone directory, 
and (c) members of a golfing club. It is desirous 
to have a complete and updated sample frame list 
that conforms to the target population of study. 
Population validity is said to be established when 
the accessible population represents the target 
population. 
It should enable the calculation of an individual’s 
Summary
This essay discusses factors considered by 
researchers when developing a sampling plan 
including the frame, sampling unit, sample size, 
target population, precision, and stratification. The 
sampling methods of probability, both simple and 
systematic were also defined and compared on their 
utility for sampling populations. The usefulness of 
sampling as applied in a quantitative survey study 
is illustrated by evaluating an article using the 
characteristics of comprehensiveness, probability 
of selection, and efficiency.