Which sample type ensures a fair representation of the entire population during data collection?

Random sampling is the method that ensures a fair representation of the entire population during data collection. In this technique, every individual or unit in the population has an equal chance of being selected. This approach minimizes bias and allows for the collection of data that is truly reflective of the larger group being studied. It is applicable in various scenarios, from surveying public opinions to conducting scientific studies, making it a fundamental aspect of research to achieve generalizable results.

Systematic sampling, while structured and useful in certain cases, involves selecting samples based on a fixed pattern or interval, which can inadvertently introduce bias if there are underlying patterns in the population. Ballot sampling refers to a technique mostly used in voting or polling contexts, not for general data collection. Predictive sampling involves collecting data intended to forecast future outcomes rather than represent the populace as it exists, making it unsuitable for ensuring fair representation.