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• Levels of measurementthese can be split into two groups: qualitative and quantitative

• data.

• They are very intuitive, so don’t worry.

• Qualitative data can be nominal or ordinal.

• Nominal variables are like the categories we talked about just nowMercedes, BMW

• or Audi, or like the four seasonswinter, spring, summer and autumn.

• They aren’t numbers and cannot be put in any order.

• Ordinal data, on the other hand, consists of groups and categories but follows a strict

• order.

• Imagine you have been asked to rate your lunch and the options are: disgusting, unappetizing,

• neutral, tasty, and delicious.

• Although we have words and not numbers, it is obvious that these preferences are ordered

• from negative to positive, thus the data is qualitative, ordinal.

• Okay, so what about quantitative variables?

• Well, as you may have guessed by now, they are also split into two groups: interval and

• ratio.

• Intervals and ratios are both represented by numbers but have one major difference.

• Ratios have a true zero and intervals don’t.

• For example, length is a ratio variable.

• You all know that 0 inches or 0 feet means that there is no length.

• With temperature, however, we have a different story.

• It is usually an interval variable.

• Let me explain.

• Usually, it is expressed in Celsius or Fahrenheit.

• They are both interval variables.

• 0 degrees Celsius or 0 degrees Fahrenheit don’t not mean anything, as the absolute

• zero temperature is actually -273.15 degrees Celsius, or -459.67 degrees Fahrenheit.

• However, we can easily say that 80 degrees Fahrenheit is less than 100 degrees Fahrenheit.

• In the case of interval variables, the difference is meaningful, but the 0 is not.

• Continuing this temperature example, there is another scaleKelvin’s.

• According to it, the absolute minimum temperature is 0 degrees Kelvin.

• Therefore, if the degrees are stated in Kelvin’s the variable will be a ratio.

• So.

• Numbers like 2, 3, 10, 10.5, Pi, etc. can be both interval or ratio, but you have to

• be careful with the context you are operating in.

• Alright!

• Weve quickly gone through the types of data and the measurement levels.

Levels of measurementthese can be split into two groups: qualitative and quantitative

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# Data Science & Statistics: Levels of measurement

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林宜悉 posted on 2020/03/09
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