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> | + | 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,