Download SCIENTIFIC RESEARCH METHODS Hand Outs Methods used in

SCIENTIFIC RESEARCH METHODS
Hand Outs
Methods used in probability sampling
Simple random sampling:
A simple random sample is a subset of individuals (a sample) chosen from a larger set
(a population). Each individual is chosen randomly and entirely by chance, such that each
individual has the same probability of being chosen at any stage during the sampling process
Systematic random sampling:
A type of probability sampling method in which sample members from a larger population are
selected according to a random starting point and a fixed, periodic interval. This interval, called
the sampling interval, is calculated by dividing the population size by the desired sample size.
Stratified random sampling:
Stratification is the process of dividing members of the population into homogeneous
subgroups before sampling. The strata should be mutually exclusive: every element in the
population must be assigned to only one stratum. The strata should also be collectively
exhaustive: no population element can be excluded. Then simple random
sampling or systematic sampling is applied within each stratum. This often improves the
representativeness of the sample by reducing sampling error.
Multistage Cluster sampling:
Cluster sampling is a sampling technique where the entire population is divided into groups, or
clusters. All observations in the selected clusters are included in the sample. Cluster sampling
is typically used when the researcher cannot get a complete list of the members of a population
they wish to study but can get a complete list of groups or 'clusters' of the population. It is also
used when a random sample would produce a list of subjects so widely scattered that surveying
them would prove to be far too expensive, for example, people who live in different postal
districts in the UK.
It is a complex form of cluster sampling. Using all the sample elements in all the selected
clusters may be prohibitively expensive or unnecessary. Under these circumstances, multistage
cluster sampling becomes useful. Instead of using all the elements contained in the selected
clusters, the researcher randomly selects elements from each cluster. Constructing the clusters
is the first stage. Deciding what elements within the cluster to use is the second stage. The
technique is used frequently when a complete list of all members of the population does not
exist and is inappropriate.
Non – Probability Sampling
Convenience Sample:
A convenience sample is one of the main types of non-probability sampling methods. A
convenience sample is made up of people who are easy to reach. Sometimes known
as grab, convenience sampling or opportunity sampling is a type of non-probability
sampling which involves the sample being drawn from that part of the population which is
close to hand. That is, a sample population selected because it is readily available and
convenient, as researchers are drawing on relationships or networks to which they have easy
access. The researcher using such a sample cannot scientifically make generalizations about the
total population from this sample because it would not be representative enough.
Snow Ball Sampling:
Snowball sampling or chain sampling, chain-referral sampling, referral sampling is a nonprobability sampling technique where existing study subjects recruit future subjects from
among their acquaintances. Thus the sample group appears to grow like a rolling snowball. As
the sample builds up, enough data is gathered to be useful for research. This sampling
technique is often used in hidden populations which are difficult for researchers to access;
example populations would be drug users. As sample members are not selected from
a sampling frame, snowball samples, people who have many friends are more likely to be
recruited into the sample.
Quota Sampling:
A sampling method of gathering representative data from a group. In Quota sampling the
representative individuals are chosen out of a specific subgroup. For example, a researcher
might ask for a sample of 100 females, or 100 individuals between the ages of 20-30 or an
interviewer may be asked to sample 200 females and 300 males between the age of 45 and 60.