| 11. | The peak and tails fit a gaussian distribution.
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| 12. | Apart from further chi-squared based characteristics like residuals follow a Gaussian distribution.
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| 13. | Outliers are given higher weight precisely because they are unlikely to occur under Gaussian distribution.
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| 14. | Quantum dots are valued for displays, because they emit light in very specific Gaussian distributions.
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| 15. | The previous example of a mixture of two Gaussian distributions can demonstrate how the method works.
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| 16. | For the Gaussian distribution case has " N " in the denominator as well.
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| 17. | :The area under the curve of a gaussian distribution is always one for every curve.
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| 18. | Where \ Phi ( x ) is the cumulative distribution function of the normal Gaussian distribution.
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| 19. | :Squaring the errors is the maximum likelihood estimate given an assumption of a Gaussian distribution.
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| 20. | The variables have a joint Gaussian distribution and are stochastically independent if the original process is Gaussian.
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