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2. A random sample is in general a representative sample for a
3. There is no need for the thorough knowledge of the units of
4. The accuracy of a sample can be tested by examining another
sample from the same universe when the universe is
5. This method is also used in other methods of sampling.
1. Preparing lots or using random number tables is tedious when
the population is large.
2. When there is large difference between the units of
population, the simple random sampling may not be a
3. The size of the sample required under this method is more
than that required by stratified random sampling.
4. It is generally seen that the units of a simple random sample
lie apart geographically. The cost and time of collection of
data are more.
2.5.2 Stratified Random Sampling:
Of all the methods of sampling the procedure commonly
used in surveys is stratified sampling. This technique is mainly
used to reduce the population heterogeneity and to increase the
efficiency of the estimates. Stratification means division into
groups.In this method the population is divided into a number of
subgroups or strata. The strata should be so formed that each
stratum is homogeneous as far as possible. Then from each stratum
a simple random sample may be selected and these are combined
together to form the required sample from the population.
Types of Stratified Sampling:
There are two types of stratified sampling. They are
proportional and non-proportional. In the proportional sampling
19 equal and proportionate representation is given to subgroups or
strata. If the number of items is large, the sample will have a higher
size and vice versa.
The population size is denoted by N and the sample size is
denoted by ‘ n’ the sample size is allocated to each stratum in such a
way that the sample fractions is a constant for each stratum. That is
given by n/N = c. So in this method each stratum is represented
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