Sampling And its types

2. DEPARTMENT OF COMPUTER SCIENCE
AND SOFTWARE ENGINEERING
MISS RABIYA

3. SAMPLING
Presented to : ma’am Rabbia

4. PRESENTED BY:
LAIBA BATOOL 3095
RIMSHA QAISER 3112
HIRA BARLAS 3126
QANDEEL ZAINAB 3080
TANIA RASHID 3056

5. SAMPLING
Statistical procedure
Concerned with the selection of individual observation
Helps to make statistical inference about population
Process of choosing a representative sample from target
population

6. SAMPLING
Sampling is of two types
Probability sampling
Non probability sampling
It should not be confused with sample

7. PURPOSE OF SAMPLING
To understand the population
To gather data about the population
To accurately describe the parameters of population
To save time and money
To estimate some indicator
To identify participants

8. TYPES OF SAMPLING

9. Probability Sampling
• Every unit has equal chance being selected for sample
• Random Sampling
• Drawing names from hat or choosing the short straw
Types Of Probability Sampling
1.Simple Random Sampling
2.Systematic Random Sampling
3.Stratified Random Sampling
4.Cluster Random Sampling
5.Multi-stage Random Sampling

10. 3. Stratified Random Sampling
• Population is divided in two or more groups called strata
• A sample is selected from each stratum
Types of Stratified Random Sampling
• Proportionate Stratification
• Disproportionate Stratification
4. Cluster Random Sampling
• Population divided to subgroups (“clusters”)
• A simple random sample is taken
• Used when population is too large

11. 1. Simple Random Sampling
• Get a list of “sample frame”
• Generate random numbers
• Select one unit per random
number
2.Systematic Random Sampling
• Order all units in sampling
frame
• Select the kth unit

12. 5.Multi-stage Sampling
• Combination of all types
• Involve selecting a sample in at least
two stages
I. Systematic and Stratified
II. Cluster and Simple Random

13. NON- PROBABILITY SAMPLING
Non Probability sample method in
which some elements of population
have no chance of selection
Types
 Convenience sampling
 Snowball sampling
 Purposive sampling
 Quota sampling

14. 1) Convenience Sampling
A type of sampling where the element
selection is based on ease of accessibility
2) Snowball Sampling
The research starts from the key person
and introduce the next one to become a
chain

15. 3) Purposive sampling
The sample based on his or her judgment
about some appropriate characteristics
required of the sample member
4)Quota sampling
In Quota sampling, a population is first
segmented into mutually exclusive sub
groups, just as in stratified sampling

16. ADVANTAGES AND
DISADVANTAGES

17. ADVANTAGES OF SAMPLING:
• Low cost of sampling.
• Less time consumed in sampling.
• Much easier to collect
information.
• Accuracy of data is high.
• Suitable in limited resources.

18. DISADVAN TAGES OF SAMPLING:
• Chances of biasness.
• Difficulties in selecting a truly
representative sample.
• In adequate in the subject.
• Impossibility knowledge of
sampling.
• Changeability of unit.

19. Sampling Errors

20. Sampling Errors
 The errors which arise due to the use of sampling surveys are known as
sampling errors.
Types of sampling errors
Biased errors:
 due to selection of sampling techniques,
 size of the sample.
Unbiased errors/ Random sampling errors:
 difference between the members of the population included or not
included
 Increasing the sample size will reduce this type of error

21. Non Sampling Errors
 Due to sample observations being selected improperly
Types of non sampling error:
Errors in data acquisition
 Due to incorrect measurement being taken
 Inaccurate recording of data
Non response error
 When units selected as part of the sampling procedure do not respond in wkole
or in part
Selection bias
 when some members of target population cannot possibly selected for inclusion
in sample
 Increasing the sample size will not reduce this type of error

22. YOU CAN’T LEARN UNTILL YOU
QUESTION IT !