2. Sampling technique  It is a procedure where we select a group of subjects (a sample) for study from a larger group (a population)

3. Why do sampling  A large proportion of individuals or items or units have to be studied, we take a sample  Easier and economical to study sample than the whole population  Items in the sample are representative of the whole population to be studied

4. Target population The population to which the investigator wishes to generalise

5.  The population of sampling units from which we draw our sample.  For practical reasons, the study population is often more limited than the target population Study population (Survey population)

6. Sample  A subset of the population, selected so as to be representative of the larger population

7. Sampling  Sampling frame: The set of sampling units from which a sample is to be selected. E.g. a list of names, or places etc.

8. Sampling  Sampling unit: The unit of selection in the sampling process. E.g. a person, a household or a district. It is not necessarily the unit of observations or study

9. Sampling  Sampling error A difference that occurs purely by chance between the value of a sample statistic and that of the corresponding population parameter

10. Types  A probability sampling : in which every unit in the population has the same chance or probability of selection.  Non probability sampling : is any sampling method where some elements of the population have no chance of selection

11. Factors commonly influencing the choice between these types include:  Nature and quality of the frame  Availability of auxiliary information about units on the frame  Accuracy requirements, and the need to measure accuracy  Whether detailed analysis of the sample is expected  Cost/operational concerns

12. Probability Sampling

13. Simple random sampling  Each element of the frame thus has an equal probability of selection  Minimizes bias and simplifies analysis of result  SRS can be vulnerable to sampling errors may result in a sample that doesn't reflect the makeup of the population(male : female)

14.  Advantages: 1. Easy to estimate the accuracy of results 2. Easy &simply  Disadvantages: 1. A sample that doesn't reflect the makeup of the population. 2. It does not provide subsamples of the population.

15. Systematic sampling  relies on arranging the target population on ordered list and then selecting elements at regular intervals.  Advantages: 1. It is easy to implement. 2. the stratification can make it efficient.

16.  Disadvantages: 1. The sample likely to be unrepresentative, making the study less accurate 2. Difficult to quantify that accuracy.

17. Stratified sampling  The population frame can be organized by categories into separate strata. Then individual elements can be randomly selected.  Potential benefits: 1. Enable researchers to draw inferences about specific subgroups. 2. Can lead to more efficient statistical estimates. 3. Enabling researchers to use the data collection approach best suited for each subgroup.

18.  Potential drawbacks: 1. Increase the cost and complexity of sample selection. 2. Can potentially require a larger sample than would other methods.

19.  A stratified sampling approach is most effective when: 1. Variability within strata are minimal. 2. Variability between strata are maximum.

20. Cluster sampling  To select respondents in groups ('clusters'). Sampling is clustered by geography, or by time periods.  It requires a larger sample than SRS to achieve the same level of accuracy.  It is commonly implemented as multistage sampling  Advantages: 1. Can reduce travel and administrative costs. 2. Does not need a sampling frame.

21. Non Probability Sampling

22. Convenience sampling  This sample would not be representative enough.  This type of sampling is most useful for pilot testing.

23. Quota sampling  One of non-probability sampling.  The population is first segmented into mutually exclusive sub-groups.  Then selection of the sample ( which is non- random) based on a specified proportion.  Disadvantage: These samples may be biased.

24. Panel sampling  Is the method of first selecting a group of participants through a random sampling method, then each participant is given the same survey or interview at two or more time points.