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Suppose one hundred eleven people who shopped in a special t-shirt store were asked the number of t-shirts they own costing more than each.

Sampling is the process of learning about a population based on a sample selected from the population of interest in statistics. This sample can be chosen in a variety of ways. The following are some of the most important methods:

a. Simple random sampling

b. Stratified sampling

c. Cluster sampling

d. Convenience sampling

Random sampling at the most basic:

In simple random sampling, every unit of the population has an equal probability of being included in the sample. The sample is chosen at random by the researcher using various procedures such as a random number table and the lottery method.

Stratified sampling:

In this method of sampling, the investigator divides the entire population into homogeneous groups depending on particular criteria, and then selects a sample from each of these stratas at random.

Cluster sampling is a technique in which a group of people Cluster sampling is a technique in which the investigator divides the population into many clusters and then selects some of the clusters at random. All members of the selected clusters are investigated.

Sampling at your leisure:

It's a method of sampling that isn't done at random. Subjects that are readily available are chosen in this form of sampling. For example, an online poll was performed to gauge public opinion on the introduction of a new product to the market. The data for the given question was gathered by interviewing the first 111 persons who entered the store.

As a result, the sample method chosen was convenience sampling.