Understanding Populations and Samples

Front

What is a population in statistics?

Back

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

Front

What is a sample in statistics?

Back

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

Front

Why do we use samples instead of populations in statistics?

Back

Because samples are easier and less costly to study.

Front

What is random sampling?

Back

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

Front

What is the main goal of random sampling?

Back

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

Front

What is a non-random sample?

Back

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

Front

What is the main disadvantage of using a non-random sample?

Back

It may not accurately represent the population.

Front

What can happen if a sample is not representative of the population?

Back

The results may be biased.

Front

What is sampling bias?

Back

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

Front

What is the difference between qualitative and quantitative data?

Back

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