Probability Sampling and Types by Selbin Babu

The presentation will cover probability sampling and all the types of probability sampling like Random sampling , systematic random sampling, strtified random sampling, cluster random sampling and multi stage sampling.

1. Probability Sampling And Types of Probability Sampling BY Selbin Babu

2. Probability Sampling Probability sampling is a sampling technique wherein the samples are gathered in a process that gives all the individuals in the population equal chances of being selected.

3. Types of Probability Sampling Random Systematic Stratified Cluster Multi-Stage Sampling Random Random Random Sampling Sampling Sampling Sampling

4. Random Sampling A  random sample is a subset of a statistical population in which each member of the subset has an equal probability of being chosen. A simple random sample is meant to be an unbiased representation of a group.

5. Example of Random Sampling The total workforce in organisations is 300 and to conduct a survey, a sample group of 30 employees is selected to do the survey. In this case, the population is the total number of employees in the company and the sample group of 30 employees is the sample.

6. Systematic Random Sampling Systematic random sampling is a type of probability sampling technique. With the systematic random sample, there is an equal chance (probability) of selecting each unit from within the population when creating the sample.

7. Example of Systematic Random Sampling For example, the researcher has a population total of 100 individuals and need 12 subjects. He first picks his starting number, 5. Then the researcher picks his interval, 8. The members of his sample will be individuals 5, 13, 21, 29, 37, 45, 53, 61, 69, 77, 85, 93.

8. Stratified Random Sampling Stratified Random Sampling is also known as proportional random sampling. This is a probability sampling technique wherein the subjects are initially grouped into different classification such as age, socioeconomic status or gender.

9. Example of Stratified Random Sampling Let’s say, 100 ( N h ) students of a school having 1000 (N) students were asked questions about their favorite subject. It’s a fact that the students of the 8th grade will have different subject preferences than the students of the 9th grade.

10. Cluster Random Sampling In cluster sampling, instead of selecting all the subjects from the entire population right off, the researcher takes several steps in gathering his sample population .

11. Example of Cluster Random Sampling A researcher may be interested in data about city taxes in Florida. The researcher would compile data from selected cities and compile them to get a picture about the state. The individual cities would be the clusters in this case

12. Multi Stage Sampling Multi-stage sampling (also known as multi-stage cluster sampling ) is a more complex form of cluster sampling which contains two or more stages in sample selection. In simple terms, in multi-stage sampling large clusters of population are divided into smaller clusters in several stages in order to make primary data collection more manageable.

13. Example of Multi Stage Sampling The  Census Bureau  uses multistage sampling for the U.S. National Center for Health Statistics’ National Health Interview Survey (NHIS). A multistage probability sample of 42,000 households in 376 probability sampling units (PSUs are usually counties or groups of counties), which are chosen in groups of around four adjacent households.