Direct comparison
Quantitative vs Categorical Variables Explained
Quantitative vs categorical variables: how to tell them apart, why a numeric code can still be categorical, and worked examples from Minitab and OpenStax.
Written and maintained by CASRAI Editorial Board
Last updated
Ask CASRAI · free to try
Ask about Quantitative vs Categorical Variables Explained
Ask your first 2 questions free below. Subscribers get 150 a day for $29 a month.
An AI assistant specialized in research administration. It cites the sources behind every answer, labels web answers and says when it can't answer.
Answers draw on CASRAI's guides and dictionary plus the federal and funder documents we index: Federal Register, Grants.gov, Regulations.gov and UKRI.
Works on this site and inside Claude, Cursor and the AI tools you already use.
Everything CASRAI publishes — this page, the dictionary, the guides and the news — stays free to read, with no account and no card.
How do Categorical variable, Quantitative variable compare side by side?
The table below compares Categorical variable, Quantitative variable across 10 procurement-relevant dimensions, from definition through source.
Side-by-side comparison
| Dimension | Categorical variable | Quantitative variable |
|---|---|---|
| Definition | Its values are mutually exclusive categories or groups (Minitab). | Its values are numbers that usually represent a count or a measurement (Minitab). |
| What the data describe | Categorizing or describing attributes of a population; also often called qualitative data (OpenStax). | Always numbers, from counting or measuring something (OpenStax). |
| Typical examples | Hair color, blood type, ethnic group, the car a person drives (OpenStax); payment method such as cash or credit (Minitab). | Amount of money, pulse rate, weight, number of people living in your town (OpenStax); number of customer complaints, fill weight of a cereal box (Minitab). |
| Subtypes named by the sources | Values can be text (cash or credit), numeric codes, or date/time values such as days of the week or months of the year (Minitab). | Discrete, the result of counting (phone calls per day); or continuous, from measuring, and may include fractions and decimals, such as lengths, weights and times (OpenStax). Date/time values such as the date and time a payment is received also count (Minitab). |
| Numeric codes | A number can be only a label: Gender (1 = Female, 2 = Male) and survey results (1 = Agree, 2 = Neutral, 3 = Disagree) are categorical (Minitab). | The number itself is the count or measurement, such as the number of customer complaints or the fill weight of a cereal box (Minitab). |
| Role in an analysis | Often used to group or subset the data in graphs or analyses (Minitab). | Values are counts or measurements, such as sale price or paint thickness (Minitab). |
| Same subject, both kinds | Appliance sales: appliance type, make and model. Painting: paint flaws, paint colors (Minitab). | Appliance sales: sale price. Painting: metal temperature, paint thickness (Minitab). |
| Recording versus reporting | Quiz scores recorded as numbers can be reported categorically as letter grades A to F (OpenStax). | The recorded quiz score is the number itself, collected as data (OpenStax). |
| When to treat a variable as each | Treat it as categorical when each value names a group, even if the group is written as a number, a date part or a code. | Treat it as quantitative when each value is a count or measurement of something. |
| Source | Minitab Support, Comparison of categorical and quantitative variables; OpenStax Introductory Statistics 2e, section 1.2 (both read 2026-10-29). | Minitab Support, Comparison of categorical and quantitative variables; OpenStax Introductory Statistics 2e, section 1.2 (both read 2026-10-29). |
