STRATIFIED RANDOM
SAMPLING
BY GROUP 4
What is Stratified Random Sampling?
Stratified Sampling is a random
sampling technique in which
the population is first divided
into strata and then samples
are randomly selected
separately from each stratum.
When would you use stratified random
sampling?
Stratified random sampling is often used when researchers want
to know about different subgroups or strata based on the entire
population being studied. Use this method when you suspect
that the group means are different, and the goal of your study
is to understand these differences.
It is mainly used in qualitative research.
ADVANTAGES
The main advantage of stratified
random sampling is that it captures
key population characteristics in
the sample.
 This method of sampling produces
characteristics in the sample that are
proportional to the overall
population.
DISADVANTAGES
 Several conditions must be met for
it to be used properly.
Researchers must identify every
member of a population being studied
and classify each of them into one, and
only one, subpopulation.
 Finding an exhaustive and definitive
list of an entire population can be
challenging.
Proportionate Stratified Random
Sampling
 In a proportionate stratified method, the sample size of each
stratum is proportionate to the population size of the stratum.
Disproportionate Stratified Random
Sampling
 In disproportionate sampling, the analyst will over- or undersample certain strata based on the research question or study
design that they are employing.
EXAMPLES
 A researcher wants to survey the general population of a country
but wants to make sure that his results are representative of
different socio-economic levels.
You want to know the different types of coping mechanisms of the
students in Caraga Regional Science High School but you want to
make sure that your results are more precise than simple random
sampling.