It is a selection of the sample randomly from a population, without any specific conditions.Group of answer choicesRandom SamplingSystematic SamplingCluster SamplingStratified Sampling

To answer the question, we need to understand the different types of sampling methods mentioned in the given options: random sampling, systematic sampling, cluster sampling, and stratified sampling.

1. Random Sampling: This method involves selecting a sample from a population randomly, without any specific conditions. Each member of the population has an equal chance of being selected. This helps to ensure that the sample is representative of the entire population.

2. Systematic Sampling: In this method, the sample is selected by choosing every nth element from the population. For example, if we want a sample size of 100 from a population of 1000, we would select every 10th element from the population.

3. Cluster Sampling: Cluster sampling involves dividing the population into clusters or groups and then randomly selecting some of these clusters to form the sample. This method is useful when it is difficult or impractical to sample individuals directly from the population.

4. Stratified Sampling: Stratified sampling involves dividing the population into subgroups or strata based on certain characteristics. Then, a sample is randomly selected from each stratum in proportion to its size in the population. This method ensures that each subgroup is represented in the sample.

In summary, random sampling involves selecting a sample randomly from a population without any specific conditions. Systematic sampling involves selecting every nth element from the population. Cluster sampling involves randomly selecting clusters or groups from the population. Stratified sampling involves dividing the population into subgroups and selecting a sample from each subgroup.