**Interval variables are types of numeric scales in which the differences between values are of equal intervals, however, a true zero point does not exist (Lewis-Beck, Bryman & Liao, 2004).**

These variables include real number scales such as temperatures in Celsius or Fahrenheit.

Despite the order and certainty of the interval between categories, an interval variable stops short of offering a real zero point. This lack of a true zero point means comparisons of absolute magnitude are generally misleading (Katz, 2006a; De Vaus, 2001). This is also what differentiates interval variables from ratio variables (Babbie, Halley & Zaino, 2007).

**An Academic Definition:**“An interval variable has equal distances between values, but the zero point is arbitrary” (Norman & Streiner, 2008, p. 4)

## Interval Variable Examples

**1. Temperature in Celsius or Fahrenheit**

Temperature scales, the Celsius and Fahrenheit, are perfect examples of interval scales. They have equal intervals (the difference between 20°C and 30°C is the same as between 30°C and 40°C), but no true zero point as -0°C and -0°F are valid and do not signify the absence of temperature.

**2. Intelligence Quotient (IQ)**

IQ is frequently measured on an interval variable scale. While the difference between scores remains consistent, there is no “zero point” for intelligence, indicating that an IQ of 0 does not signify an absence of intelligence.

**3. SAT Scores**

Scholastic Aptitude Test (SAT) scores are typically in the interval scale. The distance between 1200 and 1300 is the same as that between 1300 and 1400, yet there isn’t an absolute zero indicating the complete lack of aptitude or knowledge.

**4. Years AD**

The scale of years AD (Anno Domini) is interval. Counting years begins not from an absolute zero point but from the designated start of the Gregorian calendar. The year 0 AD does not signify the absence of time.

**5. Latitude Degrees**

Degrees of latitude, stretching from -90° at the South Pole to 90° at the North Pole, form an interval scale. There are consistent intervals across the scale, with 90° not representing a lack of latitude.

**6. Dates**

Dates are interval variables, as the interval between any two dates is consistent. However, there is no true zero point in any calendar system.

**7. Elevations Above Sea Level**

The measure of elevations above sea level serves as an interval variable. While the intervals are consistent, there is no authentic zero point as sea level does not indicate the absence of elevation.

**8. Credit Scores**

Credit scores follow an interval variable scale. The gap between a credit score of 600 and 700 is equal to that between 700 and 800. However, a score of 0 does not represent a complete absence of creditworthiness.

**9. Shoe Sizes**

Shoe sizes, using any standardized measure, be it the US, UK or EU systems. For example in US, the difference between Size 8 and Size 9 is an increment of one unit, but zero does not suggest that the foot size is non-existent.

**10. Golf Scores**

Golf scores are measured on an interval scale. The difference between scores is uniform, yet a score of zero does not infer the absence of skill.

**11. Opinions on a Five-Point Scale**

Opinions expressed on a five-point scale (like weak, below average, average, above average, strong) are interval variables. While there is a uniform distance between the categories, there is no true zero point, indicating absolute lack of an opinion.

**12. Sound Pitch**

Sound pitches in terms of musical notes form an interval variable, having consistent differences between each note, but no zero point signaling an absence of pitch.

**13. ACT Scores**

ACT (American College Testing) scores form an interval variable. The gap between a score of 20 and 30 is identical to that between 30 and 40. However, a score of 0 does not mean the total lack of knowledge or aptitude.

**14. Minutes Past the Hour**

Minutes past the hour, be it on a digital or analog clock, form an interval variable. A consistent measure is evident in minutes, and yet the start of the hour (0 minutes) doesn’t indicate an absence of time.

**15. Passengers in a Train Car**

The number of passengers in a train car as recorded at each station is an interval variable. Even though there are equal intervals between numbers, zero does not denote an absence of space or capacity.

**16. Scores on Standard Academic Tests**

Scores obtained on common academic tests like GRE, GMAT, MCAT, form interval variables. Equal intervals exist between scores, but zero doesn’t signify an absence of knowledge or abilities.

**17. Blood Pressure**

Blood pressure readings represent an interval variable. The difference between category values are consistent, but there is no true zero point representing an absence of blood pressure.

**18. Stock Market Values**

Stock market values, along with many other financial statistics, form an interval variable. The intervals are predictable, and zero does not denote a total lack of value.

**19. Social Media Likes**

The number of likes on a social media post forms an interval variable. They can be counted accurately, but zero likes does not mean an absence of quality or relevance.

**20. Race Finishing Times**

Finishing times in a race are an interval variable. Times can be precisely measured, but a time of zero does not represent an absence of time or effort.

**21. Survey Responses on a Seven-Point Scale**

Survey responses measured on a seven-point range form an interval variable. Each point on the scale is equidistant, yet, the zero on the scale does not signify the complete lack of an opinion.

**22. Test Scores**

Scores on academic tests form an interval variable. The difference between scores is uniform, but zero does not represent a complete absence of knowledge or comprehension skills.

**23. Decibel Levels**

Decibel levels follow an interval variable scale. A consistent interval exists between units of measurement, but zero decibels does not indicate the absence of sound.

**24. pH Level**

The pH level of a solution is an interval variable. The scale has equal intervals, but a pH of 0 does not signify the absence of acidity or alkalinity.

**25. Economic Indicators**

Common economic indicators like inflation, interest rates, etc., are interval variables. The difference between rates is uniform, but a zero rate does not signify an absence of economic activity.

## Types Of Variables (Compare And Contrast)

**Interval variables are a midpoint between nominal/ordinal and ratio variables.**

The key types of variables are outlined below:

**Nominal variables:**Nominal variables represent distinct categories devoid of an inherent order or ranking (Wilson & Joye, 2016). Types of chocolate or music genres are examples of nominal variables. While they help us order and categories, it is generally not possible to perform mathematical operations on nominal variables because they are somewhat arbitrary. However, counting how many instances fall into a particular category is possible with nominal variables (this is common in cross-sectional research designs).**Ordinal variables:**Ordinal variables are like nominal variables, but the categories have a logical and intrinsic order (De Vaus, 2001). The race results of “first”, “second”, and “third” exemplify this. Unlike nominal variables, ordinal variables bear an order but the exact numerical distances or intervals between categories stay unknown or inconsistent.**Interval variables:**Interval variables are those where categories can be placed in an order and the disparities between the categories are known and consistent (Lewis-Beck, Bryman & Liao, 2004). The classic example of this form of variable is temperature gauged in degrees Celsius. Yet, there is a lack of a tangible “zero point”, so comparisons of size are difficult with this type of variable. It’s incorrect, for example, to say that 40°C is “twice as hot” as 20°C.**Ratio variables**Ratio variables are like interval variables, but incorporate a crystal-clear zero definition (Katz, 2006b; Stockemer, 2018). For example, we can think of examples like height in centimeters or weight in kilograms as ratio variables. Here, zero points to the total absence of a characteristic, making it possible to authoritatively state that, for example, “Person A is twice as tall as Person B”.

## Conclusion

Interval variables hold universal applications in research, forming an indispensable part of both descriptive and inferential statistics. Unlike their ordinal counterparts, interval variables allow for a clearer understanding of the nature of the differences between categories due to their consistent intervals, availing more sophisticated statistical techniques. However, their inherent absence of a true zero point makes absolute magnitude comparisons difficult. Hence when interpreting interval variables, it’s prudent to concentrate on differences rather than ratios. Similar to the above examples, the power of interval variables to accurately gauge real-world phenomena, from temperature readings to academic test scores, provides researchers with a potent tool to quantify meaningful differences.

## References

Babbie, E., Halley, F., & Zaino, J. (2007). *Adventures in Social Research: Data Analysis Using SPSS 14.0 and 15.0 for Windows* (6th ed.). New York: SAGE Publications.

De Vaus, D. A. (2001). *Research Design in Social Research*. New York: SAGE Publications.

Katz, M. (2006*). Study Design and Statistical Analysis: A Practical Guide for Clinicians*. Cambridge: Cambridge University Press.

Katz, M. H. (2006). *Multivariable analysis: A practical guide for clinicians*. Cambridge: Cambridge University Press.

Lewis-Beck, M., Bryman, A. E., & Liao, T. F. (Eds.). (2004). *The SAGE Encyclopedia of Social Science Research Methods (Vol. 1)*. London: SAGE Publications.

Norman, G. R., & Streiner, D. L. (2008). *Biostatistics: The Bare Essentials*. New York: B.C. Decker.

Stockemer, D. (2018). *Quantitative Methods for the Social Sciences: A Practical Introduction with Examples in SPSS and Stata*. London: Springer International Publishing.

Wilson, J. H., & Joye, S. W. (2016). *Research Methods and Statistics: An Integrated Approach*. New York: SAGE Publications.

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]