sampling, method of sampling, Probability and non-probability sampling

1. SAMPLING & CENCUS
Probability & Nonprobability
Sampling
Presented by:
Anu Thapa(700408)
Navin Mandal(700415)
Rupesh Chaudhary(700420)

2. SAMPLING
INTRODUCTION
The few selected unit is called sample and
the method of selecting the sample is
called sampling.
process of selecting sample from the
universe or target population by the
researchers

3. .
TARGET POPULATION OR UNIVERSE
The population to which the investigator
wants to generalized his results
SAMPLING UNIT
Smallest unit from which sample can be
selected

4. Demerits of sampling
technique
Less accuracy
Misleading conclusion
Needs for specialized knowledge
When sampling is not possible
In case of :-
oWhen 100% accuracy is required
oThe population is heterogeneous
o When population is very small

5. Why Sample?
Get information about large populations
Lower cost
More accuracy of results
High speed of data collection
Availability of population elements.
Less field time
When it’s impossible to study the
whole population

6. Sample Vs. Census
Sample
 Only few units of the
population is studied
 It is most suitable if
population is
homogeneous
 There is margin for
error
 Take less time man
power and money
 This is smaller in
proportion
Census
 each and every unit of
the population is
studied
 It is most suitable if
population is
heterogeneous
 It is more accurate
 Take more time man
power and money
 This is much bigger in
proportion

7. Method of Sampling
.
Method of
Sampling
Probability
Sampling
Non-
Probability
Sampling

8. Probability Sampling
 Scientific method of selecting sample
 Each unit of population has equal chance of
selection
Non-Probability Sampling
 Does not involve random selection and methods
 are not based on the rationale of probability
theory.

9. Types of probability sampling
1. Simple Random Sampling (SRS)
 Simplest method of sampling
 A random no. table or lottery method is used
to determine which units are to be selected.
 Types
oSimple random sampling without replacement
(Srswor)
oSimple random sampling with replacement (Srswr)

10. Example :
Suppose a population consists of 18 units
and a sample size of 5 is to be selected.
From the random table or lottery method,
selected random no. are 65,43,63,54,46
65/18,43/18,62/18,54/18,46/18
11,7,8,0,10:- selected as sample

11. 2.Systematic Sampling
Obtain the information from cards or
register which are in serial order.
Example: Suppose a population consists
of 440 units and a sample size of 40 is to
be selected.
K=
𝑁
n
=
440
40
=11
J=6 (Random no. taken between 1 to 11)
Now,
J,J+K,J+2K,J+3K…………………J+39K
6,17,28,39,………………………..,435
Every 11th person is selected from a list of all
population.

12. 3.Stratified Sampling
 The population is divided into two or more
groups called strata,
 according to some criterion, such as
geographical location, grade level, age,
gender or income.
 and subsamples are randomly selected from
each strata.
 Each stratum is more homogeneous then the
total population
 Stratified sampling results in more reliable
and details information

13. Types of Non –Probability
Sampling
1. Judgmental Sampling
 Based on experience & qualification of
researchers.
 This sampling also known as purposive
sampling.
 If the researcher is experience an experts it is
possible that judgment sampling may useful
results.
2. Accidental Sampling
 Pedestrian are used as sample in accidental
 This is very economical

14. .
3.Quota Sampling
 Quota is directly proportional to the size of
stratum.
4.Sequencing Sampling
 Sequencing sampling also known as acceptance
of sampling
 Sample is accepted when it confirms
specifications
5. Convenience sampling
 Telephone Sampling
 197

15. Sample Error
Sample Error (E)=
𝝈
𝒏
Where, E = Sample Error
𝝈 = Standard of Deviation
n = Sample Size
 If Sample size is less then chance of error will be
more.
 If sample size more then there will be more
wastage and Uneconomical.
 There for optimum size of sample will be selected.

16. THANK YOU
.