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Unit 4: Sampling Design
Notes
Notes Reason for Stratified Sampling
Sometimes, marketing professionals want information about the component part of the
population. Assume there are three stores. Each store forms a strata and the sampling
from within each strata is being selected. The resultant might be used to plan different
promotional activities for each store strata.
Suppose a researcher wishes to study the retail sales of products, such as tea in a universe
of 1,000 grocery stores (Kirana shops included). The researcher can first divide this universe
into three strata based on the size of the store. This benchmark for size could be only one
of the following (a) floor space (b) volume of sales (c) variety displayed etc.
Size of stores No. of stores Percentage of stores
Large stores 2,000 20
Medium stores 3,000 30
Small stores 5,000 50
10,000 100
Suppose we need 12 stores, then choose four from each strata, at random. If there was no
stratification, simple random sampling from the population would be expected to choose
two large stores (20% of 12) about four medium stores (30% of 12) and about six small
stores (50% of 12).
As can be seen, each store can be studied separately using the stratified sample.
Selection by Proportionate Stratified Sample
Assume that there are 60 students in a class of a management school, of this, 10 has to be selected
to take part in a Business quiz competition. Assume that the class has students specializing in
marketing, finance and HR stream.
The first step is to subdivide the students of the class into 3 homogeneous groups or stratify the
student population, by the area in which they are specializing.
Marketing Streaming Finance Stream HR Stream
1 32 8 11 33 34
2 36 12 13 35 37
3 40 15 17 38 39
4 43 18 20 41 42
5 46 19 21 44 45
7 47 22 24 49 48
9 60 23 25 59 58
10 57 28 26 60 56
14 50 27 29 52 51
16 53 31 30 55 54
Second step is to calculate the sampling fraction f = n/N
n = Sample size required
N = Population size
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