22 Data Types
Learning Objectives
- Identify qualitative, quantitative discrete, and quantitative continuous data
- Identify the level of measurement
Quantitative vs Qualitative (Categorical) Data
Qualitative data (or Categorical data) are the result of categorizing or describing attributes of a population.
Quantitative data are the result of counting or measuring attributes of a population. Quantitative data are always numbers.
Examples: Qualitative vs. Quantitative Data
Identify whether the following data values are quantitative or qualitative.
- Hair color
- Solution: qualitative. Hair is a category: brown, black, blond, red, etc.
- Weight of cow
- Solution: quantitative. The weight of a cow is measurable number.
- Number of homeruns in a game
- Solution: quantitative. Homeruns can be counted by a number!
- Education level
- Solution: qualitative. Education level is usually determined by degree- GED, HS diploma, Associates Degree, Bachelor’s Degree, etc.
- Time spent on a train
- Solution: quantitative
- Social security number
- Solution: qualitative. Though a SSN is a number- the number does not represent a measurable value… notice, it does not make sense to take an average of SSN or compare the “size” of one SSN to another.
- Exam scores
- Solution: quantitative. Notice, that if instead this was Exam grade- that would be qualitative (e.g., A, B, C, …).
- Temperature
- Solution: quantitative
Discrete vs Continuous Data
A discrete data is a quantitative data that can be counted by whole numbers (i.e., on your fingers!). A continuous data is a quantitative data that can be measured using any decimal number (including whole numbers, but also parts and fractions).
Example: Discrete vs. Continuous
Classify each of the following quantitative data values as discrete or continuous.
- Weight of cow
- Solution: continuous. The weight of a cow can be any number- for example 516.8 pounds.
- number of homeruns in a game
- Solution: discrete. There has to be a whole number of homeruns! You cannot have a part or fraction of a run.
- Time spent on a train
- Solution: continuous. In general, time is a continuous variable- hours can be broken into minutes, into seconds.
- Temperature
- Solution: continuous.
Attributions
- Content and structure adapted from RSCC Math 1410/1420 OER Team, 2022, CC BY 4.0.
- Portions of this content adopted form Openstax ‘Introductory Statistics’: Definitions of Statistics , Probability, and Key Terms (https://openstax.org/books/introductory-statistics/pages/1-1-definitions-of-statistics-probability-and-key-terms )
