TYPES OF SAMPLING DESIGN

1. TYPES OF
SAMPLING DESIGN

2. INTRODUCTION
Sampling is considered with the selection of a subset of
individual from within a statistical population to estimate the
characteristics of the whole population. Sampling design or a
working plan that specifies the population frame , sample size ,
sample selection and estimation method in detail.
A variety of sampling techniques are available . The one
selected depends upon the nature and relevance of the study
and the information to be dealt with . Rather the purpose of the
study determines the sampling to be adopted and finally the
fund available. The various methods of sample can be broadly
categorized into two as probability and non probability
sampling . A brief discussion about this is done here.

3. PROBABILITY / RANDOM SAMPLING
In probability sampling each member of the universe has a known
chance of being selected for the sample . The main probability
sampling methods are the following :
 Simple Random Sampling :
Here each element of the frame have an equal probability of being
selected. It is of two types :
 Lottery Method :
The elements or the items of the universe numbered or written on
separate slips and then it is drawn till we get the required sample
size.
 Random Number Table :
Here each member of the population is assigned a number and
from some random point of the table of random numbers the
random numbers are read out and items are selected till we get
enough needed sample size.

4.  Restricted Random Sampling :
The selection of sample is based on subjective constraints to add
more representativeness and meaning to the sample selected. It
includes the following :
 Stratified random sampling :
The population is divided into different segments called strata and
each stratum in a strata are homogeneous in nature . The samples
are selected either by proportionate method or by non - proportional
method.
 Systematic Sampling / Quasi Random Sampling
It is done when a complete list of population is available . Here a
sampling interval is fixed by dividing the size of the universe .
 Cluster Sampling
The population is subdivided into sampling units that are subdivided
into units until an ideal level . The sample is selected from the
lowest level.

5. Non Random Sampling / Non Probability Sampling
In this method the probability of selection cant be accurately
determined as the selection is based on the personal consideration of
the investigator. Here some elements have no chance of selection.
Some of the most popular non- probability sampling designs are :
 Sampling / Deliberate sampling :
Selection of items for the sample is based on the personal judgment
of the investigator after collecting necessary information .
 Quota Sampling :
The population under study is divided into sub units called quota ,
based on common features . Then desired size of items are selected
from each quota to form the sample space. Division and selection is
based on personal judgment of the investigator.
 Convenience Sampling / Chunk Sampling :
Here samples are obtained by selecting such units from the
population which may be conveniently located and contacted.

6. CONCLUSION
Within any of the type of frame identified before a variety of
sampling methods can be employed individually or in
combination. Factors commonly influencing the choice
between these designs includes :
 Nature and quality of the frame.
 Availability of auxiliary information about units on the frame.
 Accuracy requirements and the need to measure accuracy.
 Whether detailed analysis of the sample is expected.
 Cost for operational concern

7. BIBLIOGRAPHY
 Vineeth K.M and M.C Deleep Kumar , Research
Methodology , Kalyani Publishers (2010)
 Potti L.R , Fundamentals Of Business Statistics , Yamuna
Publications
 http://en.wikipedia.org/statitical _sampling
 http://www.epa.gov/QUALITY/qksampl.html
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8. THANK YOU