Overview
This lecture introduces the two primary types of variables in statistics: qualitative (categorical) and quantitative (numerical), and explains their subtypes and examples.
Qualitative Variables
- Qualitative variables describe categories or qualities, not numerical amounts.
- Examples include eye color, gender, religious affiliation, political organization, and academic major.
- Qualitative variables classify data based on type rather than quantity.
Quantitative Variables
- Quantitative variables measure how much or how many; they are always numerical.
- Examples include company revenue, employee age, salary, and IQ.
- Quantitative variables are divided into discrete and continuous types.
Discrete Variables
- Discrete variables can only take specific, separate values with gaps between them.
- An example is the number of rooms in a house (e.g., 2, 3, 4, but not 2.5).
Continuous Variables
- Continuous variables can take any value within a given range with no gaps.
- Examples include profit amounts and house square footage; values can be infinitely precise.
Key Terms & Definitions
- Qualitative Variable — a categorical, non-numerical variable describing the type or quality of something.
- Quantitative Variable — a numerical variable measuring amounts or quantities.
- Discrete Variable — a quantitative variable that takes only distinct, separate values.
- Continuous Variable — a quantitative variable that can take any value within an interval.
Action Items / Next Steps
- Review examples of qualitative and quantitative variables.
- Practice classifying variables as discrete or continuous.