Sampling techniques
- 1. SUBMITTED BY SUBASH KC APPLICATION No:5b4b9345ee5711e9a8cdd3dbc0d2867d Department of economic studies Central university of punjab
- 2. ACKNOWLEDGEMENT I would like to express my gratitude to the online course Acadameic writing because of which I could prepare this presentation. I also extend my sincere gratitude to the course coordinator Dr. Ajay semalty who has given a wonderful lecture on the course
- 4. Non-probability (Nonrandom) sampling Probability (Random) Sampling Sample is selected without using any probability techniques Sample is selected using some probability techniques. e.g. Convenience sampling, purposive (judgement) sampling, Snowball sampling, Quota sampling e e.g. Simple Random Sampling, Probability proportion to size, Systematic sampling, Stratified sampling, cluster sampling, multistage sampling.
- 5. Convenience Sampling Sample is taken from a group of people easy to contact or to reach. e.g. standing at a mall or a grocery store and asking people to answer questions. Generally, not recommended for research due to possibility of sampling error and lack of representation of population. But, it can be useful under certain conditions e.g. a researcher wants to study expenditure of people in shopping malls during week-ends.
- 6. Purposive sampling Researcher relies on his or her own judgment to draw a sample from the population. It is effective when only limited numbers of people can serve as primary data sources due to the nature of research design and aims and objectives. E.g. for a research analysing affects of personal tragedy (such as death of family member) on performance of senior level managers, the researcher may use his/her own judgment in order to choose senior level managers, who could particulate in in-depth interviews.
- 7. Snowball Sampling It is used where sample for the study to be selected from the population is rare and scattered in population. After the identification of initial respondent, new respondents with similar characteristics/traits are identified through referrals. It is often used in hidden populations, such as drug users, sex workers, locating some diseases among patients, terrorist affecting families, which are difficult for researchers to locate/access.
- 8. Quota Sampling The population is first segmented into mutually exclusive sub-groups (just as in stratified sampling) Then judgment/convenience is used to select the subjects or units from each segment based on a specified proportion. For example, an interviewer may be interested to sample 200 females and 300 males between the age of 50 and 60. The population will be divided into exclusive groups (age-wise), then from an age group of 50-60, the sampling will be done through convenience/judgement.
- 10. Simple Random Sampling (SRS) It is a sampling techniques in which every unit in the population has the same chance of being selected in the sample. In SRS, units from the population are drawn one by one. SRS-WR (With replacement): If the unit selected at any particular draw is replaced back in the population before the next unit is drawn, it is called as SRS-WR. There is possibility of one or more population units getting selected more than once. SRS-WOR (Without Replacement): If the sampling procedure is continued till n distinct units are selected and all repetitions are ignored, this is called as SRSWOR.
- 11. Probability Proportional to Size (PPS) In SRS, all units in the population have equal chance (equal probability) of being selected. However, units vary in size, so SRS may not be appropriate as SRS does not take into account size of the unit. In PPS, units are selected with probability proportional to a given measure of size. The size measure is the value of an auxiliary variable (say, x), which is closely related with study variable (say, y).
- 12. Stratified Sampling In stratified sampling, the population is divided into subgroups (called as strata) and then sample is independently drawn from each stratum. The strata are constructed in such a way that they are homogenous with themselves, but have maximum variability with the strata. The strata can be constructed on the basis of administrative grouping, geographical regions, some other auxiliary variable. Stratified sampling gives better representation to different cross sections of the population. So, there are little chances of exclusion of any major group of the population.
- 13. Cluster Sampling It consists of forming suitable clusters of contiguous population units and surveying all the units in a sample of clusters. It is very useful in many practical surveys, where listing of population units (from where sample is to be taken) is not available, but the same may be available for small segments of the population. It is cost saving, but less efficient as compared to other methods of sampling.
- 14. Multi-stage Sampling The procedure of sampling, which consists of first selecting the clusters and then randomly choosing a specified number of units from each selected cluster, is known as two-stage sampling. The clusters that from the units of sampling at first stage are called as first/primary stage units and the elements within clusters are known as second/secondary stage units and so on….
- 15. Systematic Sampling The method in which only the first unit is selected at random, the rest being automatically selected according to a pre-determined pattern, is known as systematic sampling. This method is useful in large surveys and where a sample is selected by field staff themselves.
- 16. feedback This course really helpful for students It help to understand what is academic writing
- 17. THANK YOU