# 1.2: An Overview of Data

**At Grade**Created by: CK-12

## Learning Objective

- Understand the difference between the levels of measurement: nominal, ordinal, interval, and ratio.

## Introduction

This lesson is an overview of the basic considerations involved with collecting and analyzing data.

## Levels of Measurement

In the first lesson, you learned about the different types of variables that statisticians use to describe the characteristics of a population. Some researchers and social scientists use a more detailed distinction, called the *levels of measurement*, when examining the information that is collected for a variable. This widely accepted (though not universally used) theory was first proposed by the American psychologist Stanley Smith Stevens in 1946. According to Stevens’ theory, the four levels of measurement are nominal, ordinal, interval, and ratio.

Each of these four levels refers to the relationship between the values of the variable.

### Nominal measurement

A *nominal measurement* is one in which the values of the variable are names. The names of the different species of Galapagos tortoises are an example of a nominal measurement.

### Ordinal measurement

An *ordinal measurement* involves collecting information of which the order is somehow significant. The name of this level is derived from the use of ordinal numbers for ranking (\begin{align*}1^{\text{st}}, \ 2^{\text{nd}}, \ 3^{\text{rd}}\end{align*}

### Interval measurement

With *interval measurement*, there is significance to the distance between any two values. An example commonly cited for interval measurement is temperature (either degrees Celsius or degrees Fahrenheit). A change of 1 degree is the same if the temperature goes from \begin{align*}0^\circ\end{align*}

### Ratio measurement

A *ratio measurement* is the estimation of the ratio between a magnitude of a continuous quantity and a unit magnitude of the same kind. A variable measured at this level not only includes the concepts of order and interval, but also adds the idea of 'nothingness', or absolute zero. With the temperature scale of the previous example, \begin{align*}0^\circ\end{align*}

## Comparing the Levels of Measurement

Using Stevens’ theory can help make distinctions in the type of data that the numerical/categorical classification could not. Let’s use an example from the previous section to help show how you could collect data at different levels of measurement from the same population. Assume your school wants to collect data about all the students in the school.

If we collect information about the students’ gender, race, political opinions, or the town or sub-division in which they live, we have a nominal measurement.

If we collect data about the students’ year in school, we are now ordering that data numerically (\begin{align*}9^{\text{th}}, \ 10^{\text{th}}, 11^{\text{th}}\end{align*}

If we gather data for students’ SAT math scores, we have an interval measurement. There is no absolute 0, as SAT scores are scaled. The ratio between two scores is also meaningless. A student who scored a 600 did not necessarily do twice as well as a student who scored a 300.

Data collected on a student’s age, height, weight, and grades will be measured on the ratio level, so we have a ratio measurement. In each of these cases, there is an absolute zero that has real meaning. Someone who is 18 years old is twice as old as a 9-year-old.

It is also helpful to think of the levels of measurement as building in complexity, from the most basic (nominal) to the most complex (ratio). Each higher level of measurement includes aspects of those before it. The diagram below is a useful way to visualize the different levels of measurement.

## Lesson Summary

Data can be measured at different levels, depending on the type of variable and the amount of detail that is collected. A widely used method for categorizing the different types of measurement breaks them down into four groups. Nominal data is measured by classification or categories. Ordinal data uses numerical categories that convey a meaningful order. Interval measurements show order, and the spaces between the values also have significant meaning. In ratio measurement, the ratio between any two values has meaning, because the data include an absolute zero value.

## Point to Consider

- How do we summarize, display, and compare data measured at different levels?

## Review Questions

- In each of the following situations, identify the level(s) at which each of these measurements has been collected.
- Lois surveys her classmates about their eating preferences by asking them to rank a list of foods from least favorite to most favorite.
- Lois collects similar data, but asks each student what her favorite thing to eat is.
- In math class, Noam collects data on the Celsius temperature of his cup of coffee over a period of several minutes.
- Noam collects the same data, only this time using degrees Kelvin.

- Which of the following statements is not true.
- All ordinal measurements are also nominal.
- All interval measurements are also ordinal.
- All ratio measurements are also interval.
- Steven’s levels of measurement is the one theory of measurement that all researchers agree on.

- Look at Table 3 in Section 1. What is the highest level of measurement that could be correctly applied to the variable 'Population Density'?
- Nominal
- Ordinal
- Interval
- Ratio

Note: If you are curious about the “does not apply” in the last row of Table 3, read on! There is only one known individual Pinta tortoise, and he lives at the Charles Darwin Research station. He is affectionately known as Lonesome George. He is probably well over 100 years old and will most likely signal the end of the species, as attempts to breed have been unsuccessful.

*On the Web*

Levels of Measurement:

http://en.wikipedia.org/wiki/Level_of_measurement

http://www.socialresearchmethods.net/kb/measlevl.php

Peter and Rosemary Grant: http://en.wikipedia.org/wiki/Peter_and_Rosemary_Grant