Overview
This lecture explains the difference between discrete and continuous numerical data, provides examples, and offers strategies for identifying each type.
Types of Numerical Data
- Numerical data is divided into discrete and continuous categories.
- Discrete numerical variables have outcomes that are only counting numbers (e.g., 0, 1, 2, 3).
- Continuous numerical variables can take any value in a range, including decimals and fractions.
Discrete Numerical Data
- Only whole numbers make sense for discrete data (e.g., number of dogs owned: 0, 1, 2).
- Examples: number of books read, dice roll outcomes, number of iPhones in a classroom, number of kittens in a litter.
- "Does one half make sense?" is a guiding question; if not, the variable is discrete.
Continuous Numerical Data
- Continuous variables can be measured to any level of precision within a range (e.g., 10.5, 25.8).
- Examples: distance, time, weight, volume, concentration of sodium, height, money (as typically used).
- If half or decimal values make sense (like half a pound), the variable is continuous.
Application Examples
- Weight of a newborn kitten: continuous.
- Number of kittens in a litter: discrete.
- Height of people in a course: continuous.
- Number of iPhones in class: discrete.
- Concentration of sodium in blood: continuous.
- Inches of rainfall in a day: continuous (measurement, not count of items).
- Total of last grocery bill: continuous, unless counting exact pennies.
Key Terms & Definitions
- Discrete Numerical Variable — a variable with only whole number outcomes (counting numbers).
- Continuous Numerical Variable — a variable with outcomes over any value in a range, including fractions and decimals.
Action Items / Next Steps
- Complete example two: label each scenario as "D" for discrete or "C" for continuous based on the provided criteria.