Levels of measurement - Ad/Dis Watch

I Procrastinate
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I can't seem to find the advantages and disadvantages for the levels of measurements (nominal, ordinal, interval and ratio data).
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iammichealjackson
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(Original post by I Procrastinate)
I can't seem to find the advantages and disadvantages for the levels of measurements (nominal, ordinal, interval and ratio data).

The level of measurement is often just a property of the natural world--- you can't parcel it down to "advantages" or "disadvantges" in a simplistic A level manner (which is probably why you can't find much about it on the internet!) :P -- Of course sometimes you can choose between different measures and there might be some advantages to choosing interval(/ratio) > ordinal > nominal (not always though).

Generally though: with nominal data you can do parametric statistics which are often more powerful. So like if you wanted to measure socio-economic status, you could make this a interval data by choosing household income, or ordinal by choosing class (upper, middle, lower).

One advantage of nominal data is that it might be easier to understand. For example "smokers are 12% more likely to die from lung cancer" is easier to understand than "every cigerate smoked increases the chance of lung cancer by .001%"...
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I Procrastinate
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(Original post by iammichealjackson)
The level of measurement is often just a property of the natural world--- you can't parcel it down to "advantages" or "disadvantges" in a simplistic A level manner (which is probably why you can't find much about it on the internet!) :P -- Of course sometimes you can choose between different measures and there might be some advantages to choosing interval(/ratio) > ordinal > nominal (not always though).

Generally though: with nominal data you can do parametric statistics which are often more powerful. So like if you wanted to measure socio-economic status, you could make this a interval data by choosing household income, or ordinal by choosing class (upper, middle, lower).

One advantage of nominal data is that it might be easier to understand. For example "smokers are 12% more likely to die from lung cancer" is easier to understand than "every cigerate smoked increases the chance of lung cancer by .001%"...
Oh, so that's why i can't find it.
You lost me at "parametric statistics"
I was told that i needed to know the strengths and weakness for nominal,ordinal, interval and ratio. For psychology py3, research methods. I'll probably find it in the textbooks at college.
Thanks for the info!
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iammichealjackson
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(Original post by I Procrastinate)
Oh, so that's why i can't find it.
You lost me at "parametric statistics"
I was told that i needed to know the strengths and weakness for nominal,ordinal, interval and ratio. For psychology py3, research methods. I'll probably find it in the textbooks at college.
Thanks for the info!
haha woops. It is definately a bit of an odd question -- there might be something in your textbook about it?

Another way of phrasing what i said is that interval data is more sensitive.

Using the example of measuring socio-economic class, household income as a measure will differentiate between people who have a household income which is (a) £30,000 and (b) £32,000, however if your using a categorical variable these would be grouped under the same "middle-class" group so you lose some infomation there!.
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I Procrastinate
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(Original post by iammichealjackson)
haha woops. It is definately a bit of an odd question -- there might be something in your textbook about it?

Another way of phrasing what i said is that interval data is more sensitive.

Using the example of measuring socio-economic class, household income as a measure will differentiate between people who have a household income which is (a) £30,000 and (b) £32,000, however if your using a categorical variable these would be grouped under the same "middle-class" group so you lose some infomation there!.
Oh ok, thanks!
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