Samples

Definition

A sample is a subset of individuals or observations from a larger population used to estimate characteristics of the whole population. Proper sampling methods are crucial to ensure that the sample accurately represents the population.

5 Must Know Facts For Your Next Test

1. Samples are used because it is often impractical or impossible to study an entire population.
2. There are different types of sampling methods, including random, stratified, and systematic sampling.
3. A good sample should be representative of the population to avoid bias.
4. The larger the sample size, the more reliable the estimates will be due to reduced sampling error.
5. Sampling can introduce various biases like selection bias if not done correctly.

Review Questions

• Why is it important for a sample to be representative of its population?
• What are some common sampling methods and how do they differ?
• How does increasing the sample size affect sampling error?

Related terms

Population:

The entire group of individuals or observations that you want to study.

Sampling Bias:

A bias in which some members of the intended population are less likely to be included than others.

Sampling Error: The difference between a sample statistic and its corresponding population parameter due to random variations in selecting a sample.