1. Sampling
Sampling is the process of selecting units (such as people and
organizations) from a population of interest so that by studying the
sample you can fairly generalize your results to the population from
which the units were chosen.
In most social research, you are interested in more than just the people
directly participating in your study. You would like to be able to talk in
general terms and not be confined to only the people in your study.
The group you wish to generalize to is called the population in your
study. This is the group you would like to sample from because this is
the group you are interested in generalizing to.
2. Probability and Non-Probability
Sampling
1) A probability sampling method is any method of sampling that
utilizes some form of random selection. There are different
probability sampling methods.
a) Simple Random Sampling – In a simple random sampling, the objective is to
select n units out of N such that each n has equal chances of being selected.
The procedure is to use table of random numbers, a computer random-
number generator, or a mechanical device to select the sample.
b) Stratified Random Sampling - also sometimes called proportional or quota
random sampling, involves dividing your population into homogeneous
subgroups and then taking a simple random sample in each subgroup
3. c) Systematic random sampling – is a sampling method where you
determine randomly where you want to start selecting in the sampling
frame and then follow a rule to select every Xth element in the
sampling frame list (where the ordering of the list is assumed to be
random).
d) Cluster (Area) Random Sampling – Divide the population in clusters,
randomly sample clusters and measure all units within sampled
clusters.
e) Multi-Stage Sampling – is Combining sampling methods
4. 2) A nonprobability Sampling does not involve random selection as
probability sampling does.
Nonprobability sampling methods are divided into two broad types:
accidental or purposive
a) Accidental, Haphazard or Convenience Sampling. One of the most
common methods of sampling goes under the various titles listed as:
accidental, haphazard, or convenience. These include: street interviews by
the journalists, use of college students in a research – convenience, use of
hospital clients in hospitals.
b) Purposive Sampling – you sample with a purpose in mind. Usually
you would be seeking one or more specific predefined groups. Purposive
sampling can be useful in situations where you need to reach a targeted
sample quickly and where sampling for proportionality is not the primary
concern.
5. Sub-Categories of Purposive
Sampling
(i) Modal Instance Sampling – In sampling, when you do a modal instance
sample, you are sampling the most frequent case, or the typical case.
This sampling approach has a number of problems: (a) how do you
know what the typical or modal case is? (b) how do you know that
those three variables—age, education, income—are the ones most
relevant for classifying the typical voter?
(ii) Expert Sampling – involves the assembling of a sample of persons with
known or demonstrable experience and expertise in some area.
(iii) Quota Sampling – you select people nonrandomly according to some
fixed quota. The two types of quota sampling are proportional and
nonproportional.
6. In proportional quota sampling, you want to represent the major
characteristics of the population by sampling a proportional amount of
each.
Nonproportional quota sampling is less restrictive. In this method, you
specify the minimum number of sampled units you want in each
category. Here, you’re not concerned with having numbers that match
the proportions in the population.
7. (iv) Heterogeneity Sampling - You sample for heterogeneity when you
want to include all opinions or views, and you aren't concerned about
representing these views proportionately. Another term for this is
sampling for diversity. It is, almost the opposite of modal instance
sampling.
(v) Snowball Sampling – you begin by identifying people who meet the
criteria for inclusion in your study. You then ask them to recommend
others they know who also meet the criteria. Snowball sampling is
especially useful when you are trying to reach populations that are
inaccessible or hard to find.
