The document discusses different methods of sampling used in statistical analysis. It defines sampling as selecting a subset of a population to make inferences about the whole population. There are two main types of sampling: probability sampling, where every unit has a chance of selection, and non-probability sampling, where the probability of selection cannot be determined. Some examples of probability sampling methods provided are simple random sampling, stratified sampling, systematic sampling, and cluster sampling. Examples of non-probability sampling include judgment sampling, quota sampling, convenience sampling, purposive sampling, and snowball sampling.

1. PRESENTING BY
GUDDU KUMAR
MBA 2ND SEMESTER
27 / 1808602

2. INTRODUCTION
Sampling is the process of selecting observations ( a sample ) to provide an adequate
description and inferences of the population.
SAMPLE
 It is a unit that is selected from population
 Represents the whole population
Population ( N )
Sample ( n )

3. Meaning of Sampling
Sampling is a process used in statistical analysis in which a predetermined
number of observations are taken from a larger population.
The methodology used to sample from a larger population depends on the
type of analysis.
Definition
Sampling is defined as the process of selecting certain members or a subset of
the population to make statistical inferences from them and to estimate
characteristics of the whole population.

4. Objective
1. Identify and define the population to be studied.
2. Identify and describe common method of sampling.
3 . To understand different methods of sampling and sample size.
4. To identify which sampling method to use to solve a problem.

5. TYPES of Sampling
PROBABILITY
SAMPLING
NON –
PROBABILITY
SAMPLING

6. Probability sampling
A probability sampling scheme is one in which every unit in the
population has a chance (greater than zero) of being selected in
the sample, and this probability can be accurately determined.
Non-probability sampling
Any sampling method where some elements of population have no
chance of selection or where the probability of selection can't be
accurately determined.

7. PROBABILITY SAMPLING
 Simple random sampling
 Stratified sampling
 Systematic sampling
 Cluster sampling
 Multi –stage sampling

8.  Simple random sampling
Each and every item of the universe has an equal chance of being
selected.
Example :- Lottery method.
 Stratified sampling
This method is used when units of the universe are
heterogeneous.
Example :- 1.Units of population are divided into different strata.
2. Choose equal proportion of the samples from each strata.

9. 1000
students
in a
college
200 Arts students
300 Commerce
students
500 Science
students
10 % sample is to be taken on the basis of
random sampling
Then 20 students in arts, 30 students in
commerce, and 50 students in science are
selected using random sampling.
This method assume equal proportion of
samples chosen from diff. strata.
So each units has equal chance of being
selected.

10.  Systematic sampling
In this method all the items are systematically arranged.
Then sample units are selected at equal intervals.
Example :- If 10 students are to be selected from 100.
First 10 would be selected at random.
Or. Every 10th item selected .
Or. Every 5th ,15th,25th ….95th item selected.
Systematically. ( selected sample diff. is equal )
 Multi-stage random sampling
When sampling procedure passes through many stages.
First- entire population is divided into stages or sub-stages.

11. From the each stage some units are selected on random sampling bas
Example:- To find out the literacy rate of U.P.
Some district will be selected randomly.
Select tehsil.
Villages or towns
Wards

12.  Cluster sampling
In this method population is divided into many groups.
Some cluster are selected on random basis.
The most common cluster used in research is geographical cluster.
1. He can divided the entire population (population of Delhi) into
cluster(cities).
2. Then select s a cluster on random basis.

13. NON - POROBABILITY SAMPLING
 Judgement sampling.
 Quota sampling.
 Convenience sampling.
 Purposive sampling.
 Snowball sampling.

14.  Judgment sampling
In this method the selection of the sample items depends on the
judgment of the investigator.
Investigators exercise his judgment in the choice and include those items in
the samples which he thinks correct.
 Quota sampling.
In this method researcher chosen representative individual
from a group.
The investigators select the individual to collect information on
their personal judgments within the quotas.
Quota sampling is a type of judgment sampling.

15.  Convenience sampling
In this method investigator select the samples according to this
choice and convenience.
Example:- When a researcher collect the data regarding current
market situation.
He will choose the market which is near to him.
 Purposive sampling
In this method researcher selects a sample based on their
knowledge about the study.
Example:- if a reporter make a report regarding the cricket world cup
games by seeking the opinion of the public.
Then he will select those samples( individuals) who have knowledge of
cricket.

16.  Snowball sampling
In this method , research participants recruit other participants
for a test or study.
This sample method is used there are a few samples and difficult
to find.
It is also known as chain – referral sampling.
Example:- data from drugs smuggling.

17. PREV. YEAR QUES.
1. If a sample of 100 is to be taken from a population of 1000 farmers consisting small and
large farmer, which of the following will be the most appropriate method ?
(A)Simple random sampling (B) Cluster sampling
(C) Stratified random sampling (D) Systematic sampling
2. Which is a random sampling method ?
(A)Quota sampling (B) Purposive sampling
(C) Systematic sampling (D)Snowball sampling

18. 3. Which is a non-probability based sampling method ?
(A)Systematic sampling (B) Stratified random sampling
(C) Quota sampling (D) Simple random sampling
4. Match the items in list 1 and list 2.
list 1 list 2
A. Simple random sampling a. non probability sampling
B. Systematic sampling b. random – choice of all items from each stratum
C. Quota sampling c. the sample units are selected at equal intervals
D. Stratified random sampling d. equal probability off each item in all trials.

19. THANK YOU