ผลต่างระหว่างรุ่นของ "Probstat/notes/chi-squared distribution"

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The chi-squared distribution is very important when we want to reason about the sample variances (See [[Probstat/notes/sample means and sample variances|notes]]).  Under that settings, we sample <math>X_1,X_2,\ldots,X_n</math> from a normal population whose mean is <math>\mu</math> and variance is <math>\sigma^2</math>.
 
The chi-squared distribution is very important when we want to reason about the sample variances (See [[Probstat/notes/sample means and sample variances|notes]]).  Under that settings, we sample <math>X_1,X_2,\ldots,X_n</math> from a normal population whose mean is <math>\mu</math> and variance is <math>\sigma^2</math>.
  
Recall that <math>\frac{X_i - \mu}{\sigma}</math> is unit normal.  Therefore,
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Recall that <math>(X_i - \mu)/\sigma</math> is unit normal.  Therefore,
  
 
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This is part of probstat.

Definition

Let be independent unit normal random variables. A random variable

is called a chi-squared random variable with degree of freedom. We also write

Wikipedia has a nice article on chi-squared distribution which also includes plots of its pdf and cdf.

Properties

Here we states important properties of the chi-squared distribution without proofs.

Expectations and variances

If is chi-squared with degree of freedom, we have that its expectation

and its variance

Sample variances

The chi-squared distribution is very important when we want to reason about the sample variances (See notes). Under that settings, we sample from a normal population whose mean is and variance is .

Recall that is unit normal. Therefore,

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