Random sampling

Definition

Random sampling is a method where every member of a population has an equal chance of being selected. It ensures that the sample represents the population accurately.

5 Must Know Facts For Your Next Test

1. Random sampling helps eliminate bias in selecting samples.
2. It provides each individual in the population an equal probability of inclusion.
3. The randomness can be achieved using techniques like lottery methods or random number generators.
4. It's essential for making valid statistical inferences about a population from a sample.
5. Random sampling is fundamental for performing hypothesis testing and estimating population parameters.

Review Questions

• What does it mean for a sampling method to be 'random'?
• How does random sampling help eliminate bias?
• Why is random sampling important for statistical inferences?

Related terms

Population:

The entire group that you want to draw conclusions about.

Sample:

A subset of individuals from the population used to estimate characteristics of the whole population.

Bias:

\text{Systematic error introduced into sampling or testing by selecting or encouraging one outcome over others.}