A simple random sample of size n consists of n individuals from the population chosen in such a way that every possible sample of size _____ has an equal chance to be selected.

Answers

A simple random sample of size n consists of n individuals from the population chosen in such a way that every possible sample of size n has an equal chance to be selected.

Concept: Simple random sampling is a type of probability sampling in which the researcher randomly selects a subset of participants from a population. Each member of the population has an equal chance of being selected.

Simple random sampling works best if you have a lot of time and resources to conduct your study, or if you are studying a limited population that can easily be sampled.

In some cases, it might be more appropriate to use a different type of probability sampling:

Systematic sampling involves choosing your sample based on a regular interval, rather than a fully random selection. It can also be used when you don’t have a complete list of the population.

Stratified sampling is appropriate when you want to ensure that specific characteristics are proportionally represented in the sample. You split your population into strata (for example, divided by gender or race), and then randomly select from each of these subgroups.

Cluster sampling is appropriate when you are unable to sample from the entire population. You divide the sample into clusters that approximately reflect the whole population, and then choose your sample from a random selection of these clusters.

nhas an equal chance to be selected.Concept:Simple random sampling is a type of probability sampling in which the researcher randomly selects a subset of participants from a population. Each member of the population has an equal chance of being selected.Systematic samplinginvolves choosing your sample based on a regular interval, rather than a fully random selection. It can also be used when you don’t have a complete list of the population.Stratified samplingis appropriate when you want to ensure that specific characteristics are proportionally represented in the sample. You split your population into strata (for example, divided by gender or race), and then randomly select from each of these subgroups.Cluster samplingis appropriate when you are unable to sample from the entire population. You divide the sample into clusters that approximately reflect the whole population, and then choose your sample from a random selection of these clusters.sampling, visithttps://brainly.com/question/28008941#SPJ4