Quantitative variables, also known as numerical variables, quantify observations and can be counted or measured (Creswell & Creswell, 2018).
Quantitative variables contrast sharply with qualitative variables, the latter of which classify data into predefined groups without quantities or measures attached to them. Quantitative variables involve a numerical output that can be analyzed with various statistical methods, providing insights into patterns, relationships, or trends pertaining to the data under study.
Quantitative data are crucial in experimental research where data can be manipulated, compared, and contrasted (Bryman & Cramer, 2011).
Types of Quantitative Variables
Quantitative variables come predominantly in two forms: discrete and continuous (Frankfort-Nachmias & Nachmias, 2008).
- Discrete Variables represent a form of quantitative variable that assumes only distinct and separate values (Frankfort-Nachmias & Leon-Guerrero, 2006). They are counted and often related to events or incidents that can be enumerated. Examples of discrete variables are the number of students in a class or the number of cars in a parking lot.
- Continuous Variables, on the other hand, can take on any value within a defined range (Christmann & Badgett, 2009). These variables are measured and can be infinitely divided into smaller parts, with individual differences meaningful and accurate. Examples include measurements like height, temperature, or time.
Quantitative Variables Examples
1. Age (Discrete Variable)
Age is a quantitative variable as it involves counting the number of years a person has lived. Although it can be segmentally measured in units smaller than a year (months, weeks, days, etc.), age is generally reported in complete years, in which case it would be a discrete variable.
2. Height in Centimeters (Continuous Variable)
Height, when expressed in centimeters, is a continuous quantitative variable. The spectrum of human height is broad, and each minute increment, even to the decimal of a centimeter, is significant and can be measured, making it a continuous variable.
3. Weight in Kilograms (Continuous Variable)
Like height, weight in kilograms is a continuous quantitative variable because it can virtually take on any value within a defined range. The smallest change in weight can be significant and informative, demonstrating the continuous nature of this variable.
4. Salary in Dollars (Continuous Variable)
Salaries, when expressed in dollars, are continuous quantitative variables – they can span a wide range and include decimal values (representing cents). Both minute and significant changes in wages can be accurately measured and are meaningful, demonstrating the continuity of this variable.
5. Number of Children (Discrete Variable)
The number of children a person has reflects a discrete quantitative variable. This data involves counting whole, indivisible units (the children) without consideration for fractions or decimals.
6. Miles per Gallon (Continuous Variable)
Fuel efficiency, measured in miles per gallon, constitutes a continuous quantitative variable. Slight numerical variations reflect meaningful differences in vehicle performance and fuel economy.
7. Test Scores (Discrete Variable)
Test scores are typically discrete quantitative variables. In many educational systems, test scores are whole numbers without fractional or decimal components, thus fitting the definition of a discrete variable.
8. Blood Pressure (Continuous Variable)
Blood pressure is a continuous quantitative variable as it can accept an infinite number of potential values within a specified range. It’s measured on a continuous scale and fractional differences can be meaningful.
9. Heart Rate (Discrete Variable)
Typically measured in beats per minute, heart rate reflects a discrete quantitative variable. Although heartbeats occur continuously over time, they’re usually counted in discrete, whole number units.
10. Years of Experience (Continuous Variable)
Years of experience is a continuous quantitative variable, as it can take any real-numbered value. While normally reported in whole years, it can also include fractional years, denoting months or even days of experience.
11. Household Size (Discrete Variable)
This measure accounts for the summation of individuals residing in a single dwelling unit. The unit of measurement is whole numbers – each person counts as a full unit. It facilitates a variety of statistical analyses like checking average family size trends or assessing dependencies between household size and economic variables such as income or energy use.
12. Distance Traveled in Miles (Continuous Variable)
The distance traveled serves as a continuous quantitative variable when measured in miles. It can include any possible value within a range, with fractional and decimal values carrying meaning and significance.
13. Cholesterol Level (Continuous Variable)
Measured in milligrams per deciliter (mg/dL), cholesterol level is a continuous quantitative variable, as it can take any value within a certain range including fractional or decimal levels.
14. Number of Products Sold (Discrete Variable)
The number of products sold is a discrete quantitative variable. It involves a count of items that cannot be fractional or decimal but only whole numbers.
15. Response Time in Seconds (Continuous Variable)
Response time, in seconds, can vary continuously, making this a continuous quantitative variable. Even a fraction of a second can make a significant difference in certain contexts, such as emergency response or competitive sports.
16. Number of Pages in a Book (Discrete Variable)
The number of pages in a book is a discrete quantitative variable. Pages are tangible, countable objects, and we always express the length of a book in terms of whole number units (pages).
Related: Quantitative Reasoning Examples
17. Monthly Utility Bills in Dollars (Continuous Variable)
This number can take on a wide range of values with significant fractions. Given that exact dollar and cent amounts are recorded, and this precise quantification reflects different levels of service usage or tariff rates, we treat expenses as a continuous variable.
18. Daily Caloric Intake (Continuous Variable)
Daily caloric intake is a continuous variable as it takes on a range of possible values, with minute differences often carrying significant meaning, particularly in the context of dietary planning or health assessments.
19. Battery Life in Hours (Continuous Variable)
Battery life is deemed a continuous variable because it’s expressed in terms of hours, and can be further expounded to minutes or seconds. Even a fraction of an hour can matter in measuring battery life.
20. Percentage of Battery Left (Continuous Variable)
The percentage of battery left is a continuous variable, as it takes any value between 0% and 100%, inclusive. Every minute change in percentage carries meaning, making it continuous.
21. Shoe Size (Discrete Variable)
As a discrete quantitative variable, shoe size involves the designation of a predefined category to an individual based on their foot’s length, width, and sometimes height. The numbering system in shoe sizes makes it discrete, as individuals fall into whole or half sizes according to a widely-accepted scale which varies by geographical region.
22. Number of Social Media Followers (Discrete Variable)
The quantity of social media followers establishes a clear discrete variable in digital marketing analyses. The number of followers forms a key metric for quantifying social reach, engagement, and popularity.
23. Number of Steps Walked in a Day (Discrete Variable)
Steps are distinctly countable events that offer a total at the end of the day, making this a discrete quantitative variable. This data can be used to set personal goals, study activity trends, or develop health and fitness recommendations.
24. Temperature in Degrees Celsius (Continuous Variable)
Temperature, as measured in degrees Celsius, is a continuous variable. It can range from very cold (negative values) to extremely hot (high positive values), and any change, however small, carries a significant difference in meaning.
25. Amount of Rainfall in Millimeters (Continuous Variable)
Rainfall, measured in millimeters, is a continuous quantitative variable. It can take on any positive value and every minute change in rainfall carries significant environmental implications.
Quantitative data quantifies the problem to understand how much there is. Guided by the appropriate use of discrete and continuous variables, researchers can reliably collect, analyze, and interpret data that provide the numerical basis of their study. This numerical foundation, when designed and implemented systematically, offers informative insights that uphold the objectivity and reliability of research findings.
Bryman, A., & Cramer, D. (2011). Quantitative Data Analysis with IBM SPSS 17, 18 & 19: A Guide for Social Scientists. New York: Routledge.
Christmann, E. P., & Badgett, J. L. (2009). Interpreting Assessment Data: Statistical Techniques You Can Use. New York: NSTA Press.
Creswell, J. W., & Creswell, J. D. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. New York: SAGE Publications.
Frankfort-Nachmias, C., & Leon-Guerrero, A. (2006). Social Statistics for a Diverse Society. SAGE Publications.
Frankfort-Nachmias, C., & Nachmias, D. (2008). Methods in Social Research. New York: Worth Publishers.
Moodie, P. F., & Johnson, D. E. (2021). Applied Regression and ANOVA Using SAS. CRC Press.
Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]