Скачать или смотреть Understanding Measurement Levels in Statistics: Nominal, Ordinal, Interval and Ratio Scale explained

The scale level (level of measurement) of variables determines evaluation and analysis methods in statistics. Reason enough to explain them and give some examples so you can recognize them in the future.

In statistics, four scales or measurement levels are known:
Nominal
Ordinal
Interval
Ratio
The last two are often summarized under the generic term metric.

Nominal scale
============
The nominal scale has the lowest scale level and describes qualitative characteristics. This means that only frequencies can be counted for the measurable characteristics.
Examples
Colors
Place of birth
Gender
Brand of the chair you are sitting on

Ordinal scale
===========
The ordinal scale is also used to describe qualitative characteristics. Frequencies can also be counted here, but there is a ranking order between the characteristic values.
Examples:
Agreement or disagreement with certain facts, so-called Likert scales
Level of education
School grades
Arbitrarily formed income classes

Interval scale
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The interval scale describes quantitative characteristics of variables. You can also count frequencies and read off a ranking, but the distances between the values can be interpreted.
Examples:
Temperature in degrees Celsius
Intelligence quotient
Date

Ratio scale
=========
Finally, there is the ratio scale, which differs from the interval scale only in that there is a natural zero point. With the interval scale, on the other hand, the zero point is set artificially or arbitrarily.
Examples
Salary in euros
Distances
Weights


⏰ Timestamp
=============
0:00 Introduction
0:10 4 scales
0:20 Nominal scale
0:35 Ordinal scale
0:56 Interval scale
1:17 Ratio scale
1:36 Overview of scales and measurable properties
1:50 Final example


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