Transcript Population and sampling techniques

POPULATION AND SAMPLING
TECHNIQUES
By
Poornima
Research Scholar
Under the Guidance of
Dr. ADITHYA KUMARI H.
Associate Professor
DOS in Library and Information Science
University of Mysore
Mysore
POPULATION AND SAMPLE
Population is the area in which the information is obtained.
Sample is a section of your population that you are actually going
to survey. It is important to have a sample that will represent
the entire population in order to minimize biases.
For example:
If you want to know how American citizens feel about the war in
Iraq. Population represents the United States and the sample
is 500 citizens selected randomly from each state.
Since the answers all over the US would greatly vary, it is
important to have everyone in the population represented in
the sample. This is usually done through random sampling,
which assumes no biases seeing as the subjects were selected at
random.
DEFINITION
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Population refers to an entire group or elements
with common characteristics
A complete set of elements (persons or objects)
that possess some common characteristic defined
by the sampling criteria established by the
researcher
Sampling is the process whereby a small
proportion or subgroup of a population is selected
for analysis
Sample refers to the small subgroup which is
thought to be representative of the larger
population
TYPES OF SAMPLING
Sampling Methods:There are two types:
1. Probability Sampling Method:
Sampling when the probability is
known - rely on randomness
2. Non-Probability Sampling Method
Probability is not known (e.g., purposive
sampling, convenience sampling, quota
sampling)
PROBABILITY SAMPLING METHODS –
A simple random sample:A simple random sample is obtained by choosing
elementary units in search a way that each unit in the
population has an equal chance of being selected.
A simple random sample is free from sampling bias. However,
using a random number table to choose the elementary
units can be cumbersome. If the sample is to be collected by
a person untrained in statistics, then instructions may be
misinterpreted and selections may be made improperly.
Instead of using a least of random numbers, data collection can
be simplified by selecting say every 10th or 100th unit after
the first unit has been chosen randomly as discussed below.
Such a procedure is called systematic random sampling.
1)
2) A stratified
sample:-
A stratified sample is obtained by independently selecting a
separate simple random sample from each population
stratum.
A population can be divided into different groups may be based
on some characteristic or variable like income of education.
Like anybody with ten years of education will be in group A,
between 10 and 20 in group B and between 20 and 30 in group
C. These groups are referred to as strata. We can then
randomly select from each stratum a given number of units
which may be based on proportion like if group A has 100
persons while group B has 50, and C has 30 you may decide
you will take 10% of each. So you end up with 10 from group
A, 5 from group B and 3 from group C.
3)
A cluster sample:-
A cluster sample is obtained by selecting clusters
from the population on the basis of simple
random sampling.
The sample comprises a census of each random
cluster selected.
For example, a cluster may be something like a
village or a school or a state. So we can decide
all the elementary schools in New Delhi as
clusters. If we want 20 schools selected to be
selected, then we can use simple or systematic
random sampling to select the schools, and
then every school selected becomes a cluster.
NON PROBABILITY SAMPLING METHODS
1) Convenience Sampling:Where the researcher questions anyone who is available. This method
is quick and cheap. However we do not know how representative the sample
is and how reliable the result.
2) Quota Sampling:Using this method the sample audience is made up of potential
purchasers of your product. For example if you feel that your typical
customers will be male between 18-23, female between 26-30, then some of
the respondents you interview should be made up of this group, i.e. a quota
is given.
3) The judgement sample:A judgement sample is obtained according to the discretion of someone
who is familiar with the relevant characteristics of the population.