1. Rayat Shikshan Sanstha’s S M Joshi college Hadapsar , Pune-28 Department Of Statistics

2. Sampling
Presented By
Miss. Amunekar Shubhangi Mahadev.

3. Session Objectives By the end of the session you will be able to:
Explain what sampling means in research
List the different sampling methods available
Have had an introduction to confidence levels and confidence intervals

4. Sampling Sample frame = the target population you wish to research
Census = all the respondents in the sample frame participating in the research
Sample = a smaller group selected from the sample frame to participate in the research
Sample method = the technique used to select the sample

5. Representativeness
The aim of any sample is to represent the characteristics of the sample frame.
There are a number of different methods used to generate a sample.
As a researcher you will have to select the most appropriate method meet the requirements of your research.

6. Sampling Sampling methods can be split into two distinct groups:
Probability samples
Non-probability samples

7. Sampling Probability Samples
Probability samples offer each respondent an equal probability or chance at being included in the sample.
They are considered to be:
Objective
Empirical
Scientific
Quantitative
Representative

8. Sampling Non Probability Samples
A non probability sample relies on the researcher selecting the respondents.
They are considered to be:
Interpretivist
Subjective
Not scientific
Qualitative
Unrepresentative

9. Probability Sampling Methods
Random Sampling
Systematic Random Sampling
Stratified Random Sampling
Cluster Random Sampling
Quota Random Sampling
Multi-Stage Sampling

10. Random Sampling
This involves selecting anybody from the sample frame entirely at random.
Random means that each person within the sample frame has an equal chance of being selected.
In order to be random, a full list of everyone within a sample frame is required.
Random number tables or a computer is then used to select respondents at random from the list.

11. Systematic Random Sampling
This selection is like random sampling but rather than use random tables or a computer to select your respondents you select them in a systematic way.
E.g. every tenth person on the college list is selected.

12. Stratified Random Sampling
An appropriate group is decided upon i.e. female, male, 16 –18 year olds and the participants are picked randomly from within the strata

13. Cluster Random Sampling
Similar to stratified sampling but the groups are selected for their geographical location
i.e. school children within a particular school.
The school is the cluster with the children being selected randomly from within the cluster

14. Quota Random Sampling
Having decided on the characteristics of the sample frame, a sample is selected to meet these characteristics.
E.g. if the sample frame is car drivers and the car driving population is 55% male and 45% female then the quota would require the same proportions.
Participants would be selected to fill this quota using the random method

15. Non-probability Sampling
Convenience Sampling
Snowball Sampling
These non-probability methods can be used in conjuncture with the cluster, quota or stratified methods, however they will remain non-probability samples

16. Convenience Sampling
This involves selecting the nearest and most convenient people to participate in the research.
This method of selection is not representative and is considered a very unsatisfactory way to conduct research.

17. Snowball Sampling
This type of sampling is used when the research is focused on participants with very specific characteristics such as being members of a gang.
Having identified and contacted one gang member the researcher asks to be put in touch with any friends or associates who are also gang members.
This type of sampling is not representative however is useful, especially where the groups in the research are not socially organised i.e. they do not have clubs or membership lists.

18. Quantitative Research - Sample Size
When conducting probability sampling it is important to use a sample size that is appropriate to the aims and objectives of the research.
There are tables recommending sample size (see de Vaus, 1996 pp 71-72) but as a general rule the smaller the total sample frame the larger the sample ratio needs to be.
A common error is to assume that the sample should be a certain percentage of the population, for example 10%. In reality there is no such relationship and it only the size of the sample that is important.
A probability sample size of 100+ is considered a large enough sample to conduct statistical analysis

19. Statistics and Samples
When presenting your research you need to be able to demonstrate, how representative of the whole population the sample data you have collected is.
There are two statistical test used to do this:
Standard Error
Confidence Levels

20. Standard Error
Using the standard deviation of the population and the sample size a statistical calculation can measure the degree of error likely to occur between the results of a sample and the results of a census, this is call the standard error.
The larger the sample the lower the standard error.
When a probability sample of 100+ is undertaken the distribution can usually be assumed to be normal
When the sample has normal distribution, we can use the z score approach to obtain confidence limits for the sample mean.

21. Confidence Levels
Confidence levels are calculated using the Central Limit Theorem
Using this and the sampling error we can then use the area below the normal distribution curve to make predictions about our sample.
As well as making predictions we can use the properties of the normal distribution curve to provide us with confidence levels
There are three confidence levels 68%, 95% and 99%

22. Confidence Levels
The concept does not mean that we are 95% sure that a single sample mean lies within these limits.
The 95% confidence limits mean that if we drew many samples, and find the mean for each, then we can expect 95% of the sample means to lie within the stated limits.
95% confidence is considered acceptable in social research, medical research often requires 99% confidence

23. Confidence Levels – Bell Curve

24. Review Can you explain what sampling means in research?
Can you list the different sampling methods available?
Have had an introduction to confidence levels and sample error?

25. Further Reading
Drummond, A. (1996) Research methods for therapists. Cheltenham, Nelson Thornes
Fielding J and Gilbert N (2000) Understanding social statistics London: Sage
Thomas J R and Nelson J K (2001) Research methods in physical activity 4th Ed, Leeds, Human Kinetics
Trochim W (2007) available at