A researcher divides his population into groups and fixes the size of the sample from each group. It is an example of

Stratified sample
Quota sample
Cluster sample
All of the above

The correct answer is A. Stratified sample.

A stratified sample is a type of probability sample in which the population is divided into groups (strata) based on one or more characteristics, and a sample is then selected from each stratum. This type of sampling is used to ensure that the sample is representative of the population, and that all groups in the population are included in the sample.

A quota sample is a type of non-probability sample in which the researcher sets a quota for each group in the population, and then attempts to select participants from each group until the quota is filled. This type of sampling is not representative of the population, and it is not recommended for research purposes.

A cluster sample is a type of probability sample in which the population is divided into groups (clusters), and then a random sample of clusters is selected. The participants in the sample are then selected from the selected clusters. This type of sampling is often used when it is difficult or expensive to list all the members of the population.

In the given question, the researcher divides his population into groups and fixes the size of the sample from each group. This is an example of a stratified sample.

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