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**Dr. Jai Singh**

**Pranshi Singh (M.Ed.)**

**SAMPLING**

Sampling is a process in

sampling allows researchers to use a small group from a larger population to make observations and determinations.

Sampling means selecting the group that you will actually collect data from in your research.

For ex.- If you are researching the opinions of students in your university, you could survey a sample of 100 student

*statistical analysis*where researchers take a predetermined number of observation from a larger population.sampling allows researchers to use a small group from a larger population to make observations and determinations.

Sampling means selecting the group that you will actually collect data from in your research.

For ex.- If you are researching the opinions of students in your university, you could survey a sample of 100 student

**TYPE OF SAMPLING**

**TYPE OF SAMPLING**

**PROBABILITY SAMPLING**

**NON-PROBABILITY SAMPLING**

Probability sampling is a sampling method that involves randomly selecting a sample, or a part of the population that you want to research. It also sometimes called random sampling.

unequal chance of being included in the sample ( non-random)

Non- probability sampling refers to the sampling process in which, the sample are selected for a specific purpose with a pre-determined basis of selection.

Non- probability sampling refers to the sampling process in which, the sample are selected for a specific purpose with a pre-determined basis of selection.

Type of probability sampling

**Simple random sampling -**In a simple random sample, every member of the population has an equal chance of being selected. Your sampling frame should include the whole population.

To conduct this type of sampling, you can use tools like random number generators or other techniques that are based entirely on chance.

Example: Simple random sampling

You want to select a simple random sample of 1000 employees of a social media marketing company. You assign a number to every employee in the company database from 1 to 1000, and use a random number generator to select 100 numbers.

**Stratified random sampling-**Stratified sampling is a method of random sampling where researchers first divide a population into smaller subgroups, or strata, based on shared characteristics of the members and then randomly select among these groups to form the final sample.

These shared characteristics can include gender, age, sex, race, education level, or income.