Sampling- Basics of testing hypothesis - sampling, essence of sampling, types of sampling

Basics of testing hypothesis -
sampling, essence of sampling, types of sampling

1. Ravinandan A P Assistant Professor Sree Siddaganga College of Pharmacy Tumkur

2. Sampling , Sampling , in simple terms, means selecting a group (a sample) from a population from which we will collect data for our research. Sampling is an important aspect of a research study as the results of the study majorly depend on the sampling technique used. So, in order to get accurate results or the results that can estimate the population well, the sampling technique should be chosen wisely. Ravinandan A P 2

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8. Sampling Methods Simple random sample Stratified random sample Cluster random sample Systematic random sample   Ravinandan A P 8

9. Simple random sample (lottery method):   Every member and set of members has an equal chance of being included in the sample. Technology, random number generators, or some other sort of chance process is needed to get a simple random sample. Example—A teachers puts students' names in a hat and chooses without looking to get a sample of students. Why it's good: Random samples are usually representative since they don't favor certain members. Ravinandan A P 9

10. Stratified random sample:  The population is first split into groups. The overall sample consists of some members from every group. The members from each group are chosen randomly. Example—A student council surveys  100  students by getting random samples of  25  freshmen,  25  sophomores,  25 juniors, and  25  seniors. Why it's good: A stratified sample guarantees that members from each group will be represented in the sample, so this sampling method is good when we want some members from every group. Ravinandan A P 10

11. Cluster random sample :   The population is first split into groups. The overall sample consists of every member from some of the groups. The groups are selected at random. Example—An airline wants to survey its customers one day, so it randomly selects 555 flights and surveys every passenger on those flights. Why it's good: A cluster sample gets every member from some of the groups, so it's good when each group reflects the population as a whole. Ravinandan A P 11

12. Systematic random sample:   Members of the population are put in some order. A starting point is selected at random Example—A principal takes an alphabetized list of student names and picks a random starting point. Ravinandan A P 12

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