**Interval data is a type of quantitative data that has a consistent order and a consistent difference between values, but lacks a true zero point (Lewis-Beck, Bryman & Liao, 2004).**

The lack of a true zero point in interval data means that one cannot make meaningful statements about the ratio of two values; for instance, saying one value is “twice as much” as another would be invalid (Katz, 2006a; De Vaus, 2001).

Temperature measured in Celsius or Fahrenheit, IQ scores, and standardized test scores are examples of interval data.

**A Scholarly Definition:**“Interval data is quantitative data that represents variables measured on a scale with equal intervals between values. Interval data has a natural order, and the differences between values are meaningful and consistent. […] In interval data, zero does not represent the absence of the characteristics being measured but is an arbitrary point on the scale.” (Das, 2023)

## Interval Data Examples

**1. Temperature Measurements**

Temperature data, such as Fahrenheit or Celsius readings, are interval because they have consistent intervals (the difference between 20°C and 30°C is the same as between 30°C and 40°C), but they lack a true zero point (0°C does not mean an absence of temperature).

**2. IQ Scores**

An IQ score represents cognitive abilities, and the difference between scores (like 100 and 110) is consistent. However, an IQ score of 0 does not mean the complete absence of intelligence, which makes it an interval scale.

**3. SAT Scores**

The scores on the SAT test are interval in nature because the difference between scores, say 1200 and 1300, is consistent across the scale. A score of 0 does not signify a complete lack of knowledge or ability, but rather just represents the lowest point on the scale.

**4. Time of Day**

Using the 24-hour clock, 14:00 represents 2 PM and 15:00 represents 3 PM, with a consistent interval. However, 00:00 doesn’t mean the absence of time, just the start of a new day.

**5. Credit Scores**

A credit score of 650 versus 750 indicates different creditworthiness levels with uniform intervals. A score of 0 doesn’t represent a total absence of creditworthiness.

**6. Altitude Above Sea Level**

When measuring mountains or the height of locations, the elevation is given in terms of feet or meters above sea level. The difference between 1000m and 2000m is the same as between 2000m and 3000m. However, 0 meters doesn’t signify the absence of height, just the sea level reference point.

**7. Longitude and Latitude**

Coordinates used to pinpoint locations on the Earth’s surface, such as degrees of longitude or latitude, are consistent across intervals. For instance, the difference between 10°N and 20°N latitude is the same as that between 20°N and 30°N. Zero degrees doesn’t mean the absence of location but merely represents the Prime Meridian (for longitude) and the equator (for latitude).

**8. Year AD (Anno Domini)**

While measuring years in the Anno Domini system, the interval between 1500 AD and 1600 AD is the same as between 1600 AD and 1700 AD. However, 0 AD does not indicate an absence of time, just a reference point in our historical dating system.

**9. PH Scale**

The pH scale measures acidity and alkalinity, where the difference between pH 5 and pH 6 is consistent with the difference between pH 6 and pH 7. But a pH of 0 doesn’t mean the absence of acidity, merely a reference point for extreme acidity.

**10. Decibel (dB) Scale**

The decibel scale measures the intensity of sound. An increase of 10 dB represents a tenfold increase in intensity. The difference between 10 dB and 20 dB is consistent with the difference between 20 dB and 30 dB. However, 0 dB doesn’t indicate the complete absence of sound, but rather the quietest sound that the average human ear can hear.

**11. Seismic S-Wave Travel Times**

In seismology, the travel times of S-waves (secondary waves) can be used to determine distances to earthquake epicenters. The difference in travel time for a wave that travels 100km is consistent with one that travels 200km. Yet, a travel time of 0 doesn’t mean the absence of travel but indicates the wave’s starting point.

**12. Wind Chill Index**

The wind chill index gives an idea of how cold it feels when considering the wind speed. The difference in the perceived temperature between a wind chill of -10°F and 0°F is the same as between 0°F and 10°F. A wind chill of 0 doesn’t represent the absence of perceived temperature but a point on the scale.

**13. Hardness Scale (e.g., Mohs scale for minerals)**

The Mohs scale measures the relative hardness of minerals. The difference between a hardness of 3 (calcite) and 4 (fluorite) is consistent with the difference between 4 (fluorite) and 5 (apatite). However, a 0 on the Mohs scale does not mean the absence of hardness, just a theoretical reference point.

**14. Bread Baking Temperatures**

Baking bread at temperatures, such as 350°F, 375°F, or 400°F, has consistent interval differences. Yet, 0°F doesn’t represent the absence of temperature but is merely a point on the Fahrenheit scale.

**15. Historical Timeline BCE (Before Common Era)**

When dating events before the year 1 CE, the interval between 1000 BCE and 900 BCE is consistent with the interval between 900 BCE and 800 BCE. However, 0 BCE doesn’t indicate an absence of time, just a demarcation between BCE and CE in our historical dating system.

## Other Types of Data

There are four types of data, summarized in the table below:

Data Type | Description | Example | Mathematical Operations |
---|---|---|---|

Nominal Data | Data categories that do not have a specific order or ranking (Wilson & Joye, 2016). They are simply used to label variables without any quantitative value. | Colors (red, blue, green), gender (male, female, non-binary), types of fruits (apple, banana, cherry). | Generally, no mathematical operations can be performed except counting (De Vaus, 2001). |

Ordinal Data | Data categories with a meaningful order, but the distances between the categories are not defined or consistent (De Vaus, 2001). | Educational levels (high school, bachelor’s, master’s, doctorate), Likert scale responses (strongly disagree, disagree, neutral, agree, strongly agree). | Can be ranked or ordered, but addition or subtraction don’t make sense. |

Interval Data | Data with a consistent order and a consistent interval between values. However, they don’t possess a true zero point (Babbie, Halley & Zaino, 2007). | Temperature in Celsius or Fahrenheit, IQ scores. | Addition and subtraction are meaningful, multiplication and division are not. |

Ratio Data | Data that possess all the properties of interval data and, additionally, have a true zero point (Das, 2023; Stockemer, 2018). | Age, height, weight. | All mathematical operations are valid. |

## 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.

Das, A. P. (2023). *Understanding Python Programming*. Arpita Priyadarshini Das.

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.

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]