| 11. | Both definitions are special cases of the scaled-inverse-chi-squared distribution.
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| 12. | It follows the chi-squared distribution.
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| 13. | The noncentral chi-squared distribution generalizes this to normal distributions with arbitrary mean and variance.
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| 14. | For number of dimensions other than 2, the cumulative chi-squared distribution should be consulted.
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| 15. | The resulting value can be compared to the chi-squared distribution to determine the goodness of fit.
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| 16. | The chi square distribution for " k " degrees of freedom will then be given by:
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| 17. | It can therefore be regarded as a generalized chi-squared distribution for even numbers of degrees of freedom.
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| 18. | Under the null hypothesis, it has approximately a chi-squared distribution whose number of degrees of freedom are
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| 19. | Other Bayesians prefer to parametrize the inverse gamma distribution differently, as a scaled inverse chi-squared distribution.
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| 20. | So wherever a normal distribution could be used for a hypothesis test, a chi-squared distribution could be used.
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