Probability sampling Techniques

1. Topic : Probability Sampling Techniques
1
Master of Public Health
PG activity – Seminar Presentation
Presented by – Akshay Dhole
MPH First Year
Semester – 1

2. CONTENT
1) What is Population, Sample and Sampling frame.
2) What is sampling
3) Purpose of Sampling
4) Types of Sampling
5) What are Probability and Non-Probability Sampling
6) Different types of Probability Sampling Techniques

3. LEARNING OBJECTIVES
 Describe about Population, Sample and Sampling frame.
 Describe what is Sampling
 Describe about Purpose of Sampling
 Differentiate between Probability sampling and Non-
Probability Sampling
 Enlist and describe the types of Probability Sampling

4. Population :-
Population is also known as universe, which means a
group of animate or inanimate units of observation about
which certain information is required.

5. SAMPLE
• A sample is a portion or part of population or universe selected in
some manner, from which data is collected regarding the required
information.
Example :- A handful of rice from a sack of 100 kg rice.
Sample
Population

6. Sampling Frame :-
It is a complete, non overlapping list of all the sampling units
in the population or universe, from which the sample is to be
drawn.

7. Sampling
Sampling is a procedure by which some member of the
population are selected and they are supposed to be
representative of the entire population.

8. PURPOSE OF SAMPLING
• Economical :- In most cases, it is not possible and economical for
researchers to study entire population with the help of sampling, the
researcher can save lots of money, time and resources to study phenomenon.
• Improve Quality of Data :- It is a proven fact that when a person handle
less amount the work of people, then it is easier to ensure the quality of
outcome.

9. PURPOSE OF SAMPLING
• Quick Study Results :- Studying an entire population itself will take a
lot of time & generating research results of a large mass will be almost
impossible as most research studies have time limits.
• Precision and Accuracy of data :- Selecting whole population will be
difficult to handle than handling the information of a small portion of
the population. It is easier to maintain quality of data with small
samples investigation rater than selecting the whole population

10. TYPES OF SAMPLING
Probability Sampling Non-Probability Sampling

11. PROBABILITY SAMPLING
A Probability sample is one in which each member of the population has
equal chance of being selected.
Non – Probability Sampling
Non Probability sample a particular member of the population being chosen
is unknown.

12. TYPES OF SAMPLING

13. SIMPLE RANDOM SAMPLING
 The method is applicable when the population is small, homogeneous and
readily available.
 The principle here is that every unit of population has equal chance of being
selected.
• There are two ways of Sampling
1) Lottery method
2) Table of random number method

14. Examples :-
Lottery method
1) Suppose, 10 patients are to be put on a trial out of the 100 available,
Note the serial number of patients on 100 cards and shuffle them well.
2) Draw out one and not the number.
3) Replace the card drawn, reshuffle and draw the second card.
4) Repeat the process till 10 numbers are drawn.
5) Reject the cards that are drawn for second time. The 10 cards drawn
thus will indicate the patient’s number to be put on trial and the 10
patients selected in this manner form the random sample.

15. Table of random number method :-

16. SYSTEMATIC RANDOM SAMPLING
• This method is popularly used in those cases when population is large,
homogeneous and a complete list of population from which sample is to be
drawn, is available.
• Systematic procedure is followed to choose a sample by taking every K th
house or patient where K refers to the sample interval, which is calculated by
the formula
k = Total Population = N
Sample size desired n

17. Example :- If 100 sample is to be taken out of one thousand population.
k = 1000 = 10
100
One random number is found by pulling out one card after shuffling, out of 10 cards serially
numbered 1 to 10.
Supposing it is 6, then the sample will consist of units with sample numbers
1 sample = 6,
2 sample =6 + 10 = 16,
3 sample =16 + 10 = 26,
4 sample = 26 + 10 = 36
and so on till 100 sample……..
Examine every 10th house after the 6th house

18. STRATIFIED SAMPLING
• This method is followed when the population is not homogeneous.
• The population under study is first divided into homogeneous groups or
classes called strata and the sample is drawn from each stratum at
random in proportion to its size.
• It is a method of sampling for giving representation to all strata of society
or population such as selecting sample from defined areas, classes, ages,
sexes, etc.

19. Example :-
1) The Entire population which may be heterogeneous in terms of education, occupation or income can
be divided into five socioeconomic groups of homogeneous population.
2) Units are chosen from each stratum to acquire the total sample size.

20. CLUSTER SAMPLING
• If the study area is a large one it can be divided into smaller non-
overlapping units known as cluster and then some of these cluster are
randomly selected to be included in the study.
• Cluster can be formed on the basis of ;
Geographical areas :- e.g. Village, town, city, etc.
Educational institutions :- e.g. school, colleges, class, etc.
Workplaces :- e.g. office, factory etc.

21. Cluster Sampling

22. MULTISTAGE SAMPLING
• As the name implies, this method refers to the sampling procedures carried out
several stages using random sampling techniques
• Example :-
1) Survey for prevalence of a disease in a district some blocks may be selected at
first stage.
2) Followed by selecting some PHC in each of the selected block at second stage.
3) Then some sub-centres in each selected PHC at third stage
4) Villages in selected sub-centre at fourth stage
5) Finally individual in the selected villages at the fifth stage

23. REFERENCES
Biostatistics K .RAO(A manual of Statistical method for use in Health, Nutrition and
Anthropology)
Mahajan’s method in Biostatistics
AH Suryakanta Community Medicine
Mahajan and Gupta Textbook of PSM
https://www.statisticshowto.com/probability-and-statistics/sampling-in-
statistics/