Advanced Topics
In a nutshell: Learn how to choose samples and design experiments for reliable results.
## Choosing Who and What to Study
Getting good data starts with choosing the right sample and designing fair experiments.
## Types of Sampling
- **Simple random sample**: Everyone has an equal chance.
- **Stratified sample**: Divide the population into groups, then sample from each.
- **Cluster sample**: Randomly select entire groups.
## Experimental Design
Good experiments control for variables and use random assignment to avoid bias. They often include:
- **Control groups**
- **Randomization**
- **Replication**
## Why It Matters
The way you gather data affects what you can conclude. Good design leads to trustworthy results.
Examples
- A pollster uses a stratified sample to ensure all age groups are represented in a survey.
- A scientist randomly assigns participants to receive a new medication or a placebo.
Key terms
- Randomization
- Assigning subjects to groups by chance to avoid bias.
- Control group
- A group that does not receive the treatment, used for comparison.