Nominal, Ordinal, Interval & Ratio Data: Simple Explanation With Examples

Learn about nominal, ordinal, interval and ratio data, also known as the four levels of measurement in statistics. We explain these levels of data in simple terms, starting from the basics of categorical and numerical data types.
Overview: Nominal, Ordinal, Interval & Ratio-Level Data
00:00 Introduction & overview
00:48 The basics: categorical and numerical data
01:06 Examples of categorical data
01:35 Examples of numerical data
02:19 Why do the levels of measurement matter?
03:01 Level 1: Nominal data
03:12 Examples of nominal data
04:30 Level 2: Ordinal data
04:45 Examples of ordinal data
05:39 Level 3: Interval data
06:05 Examples of interval data
07:34 Level 4: Ratio data
07:59 Examples of ratio data
09:03 Recap and summary
10:11 Outro
Recommended Resources:
Levels of measurement 101 (blog post) - gradcoach.com/nominal-ordinal...
Quantitative data analysis 101 - • Quantitative Data Anal...
The 5 biggest quant analysis mistakes - • Quantitative Data Anal...
How to write the results chapter for a quant study - • Dissertation Results C...
To learn more about nominal, ordinal, interval and ratio data, the four levels of measurement, check out the Grad Coach blog at gradcoach.com/blog/
For 1-on-1 help with your statistical analysis or any other aspect of your research project, check out Grad Coach’s private coaching service at gradcoach.com/dissertation-co....

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Hello emma, thanks for good explanation on the four levels of measurement in statistics i.e nominal, ordinal, interval and ratio data, keep more coming, then, can you kindly show a video on "clinical research on drug efficacy"

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[@arulanpillay6515]

Thanks so much Emma. Quick Q? If I am using a Likert scale which sounds ordinal but has a numerical number attached to each rank, example Strongly Disagree = 1 and Strongly Agree = 6, would this still be ordinal data or is it now numerical data?

[@hassanelgarras3263]

Yes. Good luck.

[@sumailaabdulkadiri3926]

It is going to be ordinal; the reason is; your Likert-scale values are categorical data depending on the type of scale for example (1. very poor 2. poor 3. acceptable 4. good 5. very good) or (1. very likely 2. unlikely 3. Neutral 4. likely 5. very likely). Given the example you sighted, there is a meaningful order in the categories and it is ranked with 1 being strongly disagreed, and 6 strongly agree.
Also, because you're assigning numbers to them (1,2,3,4,5) does not make it numerical. The number assigning is to allow easy analysis of the data because likert scale is mostly qualitative.
Hope this helps..

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I observed some researches treating likert scale as interval data...But formally likert scale is ordinal data

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Hi, can I ask, for true and false questions, it should be categorized as nominal or ordinal?

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Nominal

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Which one of the following is true about ordinal data

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what if we deal about the rank on previous grade, doesn't it deal about numerical

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I'm not 100% sure what you're asking, but chances are rank data would be ordinal.

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