Methods of sampling
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This document discusses different methods of sampling used in statistical analysis. It outlines two main types of sampling: probability sampling and non-probability sampling. Probability sampling methods like simple random sampling, systematic sampling, stratified sampling, and cluster sampling ensure each item has a known chance of being selected. Non-probability sampling relies on convenience, judgment, or quotas to choose items in a non-random fashion. The document provides details on each sampling technique and how they are applied in research.
Methods of sampling
- 1. By Dr. Satyanarayan Pandey Department of Management Studies, BBMK University, Dhanbad Methods of Sampling
- 2. What is Sampling? Sampling Sampling is the selection of a subset of individuals from, within statistical population to estimate characteristic of whole population. Sample Design: A sample design is a definite plan determined before any data is collected for obtaining a sample from a given population.
- 3. Methods of sampling There are two important Methods of sampling 1. Probability sampling 2. Non-probability sampling
- 4. Probability Sampling With probability sample each element has a known probability of being include in the sample. Probability samples are those based on Random Sampling Systematic sampling Stratified sampling Cluster Sampling
- 5. Simple Random sampling Chance sampling Each item has an equal probability of selection. In case of infinite population, the selection of each item in a random sample is controlled by the same probability and that successive selection are independent of one another.
- 6. Systematic sampling Most practical way of sampling Useful when sampling frame is available in the form of a list. In such design selection process starts by picking some points in the list and then every nth element is selected until the desired number is secured.
- 7. Stratified Sampling Used when population doesn’t constitute a homogenous group. Population is stratified into a number of non- overlapping subpopulation or strata and sample items are selected from each stratum. Stratified Random Sampling If the item selected from each stratum is based on random sampling the entire procedure, first stratification then simple random sampling known as Stratified random sampling.
- 8. Cluster Sampling Grouping the population and then selecting the group or the cluster rather than individual elements for inclusion in the sample.
- 9. Non -Probability Sampling Deliberative sampling, purposive sampling In this type of sampling, items for the sample are selected deliberately by the researcher, his choice concerning the item remains supreme. Non probability sampling are those based on 1. Convenience sampling 2. Judgmental sampling 3. Quota sampling
- 10. Convenient sampling When population elements are selected for inclusion in the sample based on the ease of access. At times such a procedure may give biased result particularly when the population is not homogenous.
- 11. Judgmental sampling Researchers judgment is used for selecting items which he considers as representative of the population. It is used quite frequently in qualitative research where the desire happens to develop hypothesis rather than to generalize to larger populations.
- 12. Quota sampling In stratified sampling the cost of taking random sample from individual strata is often high so interviewers are simply given quota to be filled from different strata.
- 13. Thank You