Sampling Design

1. SAMPLING DESIGN
J. JANARDHAN

2. CENSUS AND SAMPLE SURVEY
 In any field of inquiry constitute a ‘Universe’ or ‘Population’
 A complete enumeration of all items in the ‘population’ is known
as a census inquiry
 many a time it is not possible to examine complete population
 Sometimes, it is possible to obtain sufficiently accurate results by
study only a part of total population

3. STEPS IN SAMPLE DESIGN
 The researcher must pay attention in Sample design
(i) Type of universe (ii) Sampling unit (Sta, Dis, Md, Vi)
(iii) Source list (iv) Size of sample:
(v) Parameters of interest (vi) Budgetary constraint:
(vii) Sampling procedure

4. CHARACTERISTICS OF
SAMPLE DESIGN
 (a) Sample design must result in a truly representative sample
 (b) It must be such which results in a small sampling error
 (c) it must be viable in the context of funds
 (d) It can be controlled in a better way
 (e) The results of the sample study can be applied, in general, for
 the universe with a reasonable level of confidence

5. DIFFERENT TYPES
 There are different types of sample designs
probability sampling
non-probability sampling
 Probability sampling is based on the concept of random selection
 non-probability sampling is ‘non-random’ sampling
 non-probability sampling is also having different types
deliberate sampling,
purposive sampling
judgment sampling
Quota sampling

6. PROBABILITY SAMPLING
 Every item of the universe has an equal chance
 By a lottery, individual units are picked up whole group
 we can measure the errors of estimation or the significance
 of results
 This fact brings out the superiority of random sampling design
 (a) It gives equal priority to each element in the population
 (b) It gives each possible sample combination an equal probability
of being chosen

7. SIMPLE RANDOM SAMPLING
 It is also known as chance sampling
 Each and every item in the population has an equal chance
 For instance, you want to select 100 clients to survey
 If there were 1000 clients over the past 12 months
 Then, the sampling fraction is f = n/N = 100/1000 = .10 or 10%

8. STRATIFIED RANDOM SAMPLING
 It is used when the population does not constitute a homogeneous
group
 Under this sampling the population is divided into several sub-
populations ( ‘Strata’)
 We select items from each stratum to constitute a sample
 Since each stratum is more homogeneous than the total population
 We are able to get more precise estimates for each stratum
 Stratified sampling results in more reliable and detailed
information

9. SYSTEMATIC RANDOM SAMPLING
 (i) Systematic random sampling:
 The most practical way of sampling is to select every ith item on a
list.
 For instance, if a 4 per cent sample is desired,
 the first item would be selected randomly from the first twenty-
five
 Thereafter every 25th item would automatically be included in the
sample

10. SYSTEMATIC RANDOM SAMPLING
 (i) Systematic random sampling:


11. COMPLEX RANDOM SAMPLING
(iii) Cluster sampling:
 If the total area of interest happens to be a big one
 Sample can be taken is to divide the area into a number of smaller
non-overlapping areas (clusters)
 Cluster sampling, no doubt, reduces cost
 Cluster sampling is used only because of the economic advantage
 But, certainly it is less precise than random sampling
(iv) Area sampling: If clusters happen to be some geographic sub-
divisions
(v) Multi-stage sampling: Banking Sector in India

12. COMPLEX RANDOM SAMPLING
 (vii) Sequential sampling:
 This sampling design is some what complex sample design.
 The ultimate size of the sample under this technique is not fixed
in advance,
 But is determined according to mathematical decision rules on the
basis of information yielded as survey progresses

13. QUOTA SAMPLING
 Taking random samples from individual strata is often so
expensive
 that interviewers are simply given quota to be filled from different
strata
 The actual selection is left to the interviewer’s judgment
 The size of the quota for each stratum is generally proportionate
to the size of that stratum in the population
 Quota samples generally happen to be judgment samples rather
than random samples

14. DELIBERATE SAMPLING
 Deliberate sampling is also known as purposive or non-
probability sampling
 This sampling method involves purposive or deliberate selection
of particular units

15. THANK YOU