Types of Variables in Statistics for Quant Analysis?

(Last Updated On: February 24, 2012)

Types of Variables in Statistics for Quant Analysis?

Pls tell about Types of Variables in Statistics? Also, explain each of them with example. thanks

Interesting question. From what perspective are you asking? e.g. Continuous vs discrete, independant vs dependant?

 

This question makes me think of nominal, ordinal, interval & ratio. The level of measurement typically dictates what statistics can or cannot be applied.

 

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I need to use continuous functions in my work.

 

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guys, please explain each type of variable stated. thanks

 

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The most basic variable without which there is no statistics is a Random Variable: It is defined as Borel measurable function.

 

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I am afraid Borel measurable function may not help to find out a difference between such statistical variables as “gender”, “country rank” and “annual income” 🙂 The other approach is a classical one so I totally support it.

Sorry for making light of your question. But as you see, your question is really loaded with a lot of nuances. It’s an important fundamental question that needs to be asked and a really good one.

I’m a student of this discipline understand, so I’m hoping for feedback also.
But along the lines of what’s been said so far, when sampling data ideally were hoping for iid, independent and random variables. That is, each data point samples is not somehow dependent on the results of another sampled data point. There are more advance techniques available that deal with deviations from this condition. The data analysis and what your hoping to determine, such as association, homogeneity or the mean will also inpact on how you want to classify your data. That’s where continuous, , nominal, oridinal, interval, binomial,etc.play an important role.

 

 

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