Understanding Populations and Samples

A population is the entire group of individuals or items that we want to study or draw conclusions about.

A sample is a subset of individuals or items selected from a population, used to make inferences about the population.

Because samples are easier and less costly to study.

Random sampling is a technique where every individual in a population has an equal chance of being selected for the sample.

To ensure every individual has an equal chance of being selected.

A non-random sample is a sample that is not selected using random methods, which may lead to bias.

It may not accurately represent the population.

The results may be biased.

Sampling bias occurs when certain individuals or groups are overrepresented or underrepresented in a sample.

Qualitative data describes characteristics or qualities, while quantitative data involves numerical measurements.