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  2. Chi-squared distribution - Wikipedia

    en.wikipedia.org/wiki/Chi-squared_distribution

    The chi-squared distribution has numerous applications in inferential statistics, for instance in chi-squared tests and in estimating variances. It enters the problem of estimating the mean of a normally distributed population and the problem of estimating the slope of a regression line via its role in Student's t-distribution.

  3. File:Chi distribution PDF.svg - Wikipedia

    en.wikipedia.org/wiki/File:Chi_distribution_PDF.svg

    This file contains additional information, probably added from the digital camera or scanner used to create or digitize it. If the file has been modified from its original state, some details may not fully reflect the modified file.

  4. File:Chi-square pdf.svg - Wikipedia

    en.wikipedia.org/wiki/File:Chi-square_pdf.svg

    Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts.

  5. Chi distribution - Wikipedia

    en.wikipedia.org/wiki/Chi_distribution

    In probability theory and statistics, the chi distribution is a continuous probability distribution over the non-negative real line. It is the distribution of the positive square root of a sum of squared independent Gaussian random variables .

  6. Yates's correction for continuity - Wikipedia

    en.wikipedia.org/wiki/Yates's_correction_for...

    The effect of Yates's correction is to prevent overestimation of statistical significance for small data. This formula is chiefly used when at least one cell of the table has an expected count smaller than 5. = = The following is Yates's corrected version of Pearson's chi-squared statistics:

  7. File:Chi-square distributionPDF.svg - Wikipedia

    en.wikipedia.org/wiki/File:Chi-square...

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  8. Relationships among probability distributions - Wikipedia

    en.wikipedia.org/wiki/Relationships_among...

    If X 1 and X 2 are independent chi-squared random variables with ν 1 and ν 2 degrees of freedom respectively, then (X 1 /ν 1)/(X 2 /ν 2) is an F(ν 1, ν 2) random variable. If X is a standard normal random variable and U is an independent chi-squared random variable with ν degrees of freedom, then X ( U / ν ) {\displaystyle {\frac {X ...

  9. Generalized chi-squared distribution - Wikipedia

    en.wikipedia.org/wiki/Generalized_chi-squared...

    In probability theory and statistics, the generalized chi-squared distribution (or generalized chi-square distribution) is the distribution of a quadratic function of a multinormal variable (normal vector), or a linear combination of different normal variables and squares of normal variables.