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  2. Chi-squared distribution - Wikipedia

    en.wikipedia.org/wiki/Chi-squared_distribution

    For the chi-squared distribution, only the positive integer numbers of degrees of freedom (circles) are meaningful. By the central limit theorem, because the chi-squared distribution is the sum of independent random variables with finite mean and variance, it converges to a normal distribution for large .

  3. Chi-squared test - Wikipedia

    en.wikipedia.org/wiki/Chi-squared_test

    Chi-squared distribution, showing χ2 on the x -axis and p -value (right tail probability) on the y -axis. A chi-squared test (also chi-square or χ2 test) is a statistical hypothesis test used in the analysis of contingency tables when the sample sizes are large. In simpler terms, this test is primarily used to examine whether two categorical ...

  4. Pearson's chi-squared test - Wikipedia

    en.wikipedia.org/wiki/Pearson's_chi-squared_test

    The Pearson's chi-squared test statistic is defined as . The p-value of the test statistic is computed either numerically or by looking it up in a table. If the p-value is small enough (usually p < 0.05 by convention), then the null hypothesis is rejected, and we conclude that the observed data does not follow the multinomial distribution.

  5. Reduced chi-squared statistic - Wikipedia

    en.wikipedia.org/wiki/Reduced_chi-squared_statistic

    Reduced chi-squared statistic. In statistics, the reduced chi-square statistic is used extensively in goodness of fit testing. It is also known as mean squared weighted deviation ( MSWD) in isotopic dating [1] and variance of unit weight in the context of weighted least squares. [2] [3]

  6. Goodness of fit - Wikipedia

    en.wikipedia.org/wiki/Goodness_of_fit

    Pearson's chi-square test. Pearson's chi-square test uses a measure of goodness of fit which is the sum of differences between observed and expected outcome frequencies (that is, counts of observations), each squared and divided by the expectation: where: Oi = an observed count for bin i. Ei = an expected count for bin i, asserted by the null ...

  7. 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 form of a multinormal variable (normal vector), or a linear combination of different normal variables and squares of normal variables. Equivalently, it is also a linear sum of independent ...

  8. p-value - Wikipedia

    en.wikipedia.org/wiki/P-value

    Definition. The p -value is the probability under the null hypothesis of obtaining a real-valued test statistic at least as extreme as the one obtained. Consider an observed test-statistic from unknown distribution . Then the p -value is what the prior probability would be of observing a test-statistic value at least as "extreme" as if null ...

  9. Chi-square - Wikipedia

    en.wikipedia.org/wiki/Chi-square

    Chi-square. The term chi-square, chi-squared, or has various uses in statistics : chi-square distribution, a continuous probability distribution. chi-square test, name given to some tests using chi-square distribution. chi-square target models, a mathematical model used in radar cross-section.

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