Discussion
The method of systematic sampling can be alternative to
simple random sampling and specially preferred when the
information required to construct a sampling is available in
a list or any other organized form. Although systematic
sampling is used for its convenience of drawing and
execution, but its variance of estimator requires some
assumptions about the underlying population order. Some
of these assumptions are whether the population elements
follow particular order, constant mean within strata, or the
population is assumed to be either linearly increasing or
decreasing in the variable of interest.
In the light of results, systematic sampling can safely be
recommended in situations where the ordering of the
population is essentially random or contains at most a mild
stratification, for the effects of hidden periodicies tend to
cancel out when systematic sample is drawn from each
stratum.
As for a simple random sampling, it is a method which
executed in a manner that every element of the population
has equal probability of being included in the sample and a
complete frame including units of population is needed. In
addition, simple random sampling gives unbiased estimates
of population means and variances estimates .Thus, when
we do not select our sample randomly out of the population
of interest, our sampling results may be biased. Hence, the
necessity of simple random sampling arises.
It is seen that the performance of a systematic sampling
in relation to that of stratified or simple random sampling is
mainly dependent on the properties of the population. All
the evidences show that both stratified random sampling
and systematic sampling are much more effective than
simple random sampling, but generally systematic
sampling is less precise than stratified random sampling.
The systematic sampling is approximately as precise as
stratified random sampling with one unit per stratum. The
difference between the two methods is that the systematic
sample is spread more evenly over the entire population
than a stratified random sample, because in the latter, the
samples in stratified sampling the samples in the strata are
drawn separately. This adds precision in some cases.