Statistics Notation: Mean, Variance & Normal Distribution

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Discussion Overview

The discussion revolves around the notation used in statistics, specifically regarding the normal distribution, mean, variance, and the interpretation of symbols such as "~" and "N(μ, σ²)". Participants explore the meaning of these notations and their implications in describing random variables.

Discussion Character

  • Technical explanation
  • Conceptual clarification

Main Points Raised

  • One participant seeks clarification on the notation "~" in the context of random variables and their distributions.
  • Another participant explains that "~" can be interpreted as "distributed as" or "has distribution".
  • There is a discussion about the notation "N(μ, σ²)" being standard for normal distributions.
  • Participants confirm that "N(23,9)" refers to a normal distribution with a mean of 23 and variance of 9, not standard deviation.
  • One participant acknowledges a mistake regarding the interpretation of variance versus standard deviation in the notation.

Areas of Agreement / Disagreement

Participants generally agree on the meanings of the notation discussed, but there is a correction regarding the interpretation of variance and standard deviation. The discussion remains focused on clarifying these notations without significant disagreement.

Contextual Notes

Some assumptions about the understanding of statistical notation may be implicit, and the discussion does not delve into deeper mathematical implications or applications of the normal distribution.

ampakine
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In my lecture notes on confidence intervals the lecturer wrote this:
Recall that measurements tend to follow a normal distribution. To describe the normal distribution and answer useful questions (as in the previous chapter), we need to know two numbers; the expectation or mean μ and the standard deviation (square root of the variance) σ. Then the quantity we measure X follows the normal distribution:
X ~ N(μ, σ2)

I don't understand the notation of that bolded text. I know X is a random variable, μ is the population mean and σ is the population standard deviation but what does the ~ mean? Also the N(μ, σ2) I assume means normal distribution but is that some kind of standard notation for distributions? For example if I said N(23,9) would that mean the normal distribution with a mean of 23 and standard deviation of 9?
 
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ampakine said:
In my lecture notes on confidence intervals the lecturer wrote this:


I don't understand the notation of that bolded text. I know X is a random variable, μ is the population mean and σ is the population standard deviation but what does the ~ mean?

In probability theory, the notation is used to state the distribution for a random variable. You may think of the "~" as saying "distributed as" or "with distribution" or "has distribution".

Also the N(μ, σ2) I assume means normal distribution but is that some kind of standard notation for distributions?

It's a standard notation for normal distributions.

For example if I said N(23,9) would that mean the normal distribution with a mean of 23 and standard deviation of 9?

Yes
 
That clears it up. Thanks!
 
ampakine said:
For example if I said N(23,9) would that mean the normal distribution with a mean of 23 and standard deviation of 9?

Just to say it would be a normal with a mean of 23 and a variance of 9.
 
QuendeltonPG said:
Just to say it would be a normal with a mean of 23 and a variance of 9.

Yes. My mistake. The notation did use a \sigma^2 so the 9 is the variance, not the standard deviation.
 

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