If you want to be able to infer causality from your study and say that your independent variable is causing changes in yourdependent variable then you should "use a random sample of the population."
<h3>What is simple random sample?</h3>
A simple random sample is a subsection of a statistical population in which everyone has an equal chance of being selected. A simple random sample is intended to represent a group in an unbiased manner.
Some key features regarding the simple random sample are-
A simple random sample selects a small, random subset of the population to depict the entire set of data, with each member having an equal chance of being chosen.
Using methods such as lotteries or random draws, researchers can generate a simple random sample.
A sampling error may occur when a simple random sample fails to accurately represent the population it is meant to represent.
Simple random samples are created by allocating sequential values to every item in a population and then selecting those values at random.
Simple random sampling differs from systematic sampling, stratified sampling, and cluster sampling in its sampling approach.
