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CHI SQUARED-DISTRIBUTION

  • Chi-squared distribution
  • Probability distribution and special case of gamma distribution

    The chi-squared distribution χ k 2 {\displaystyle \chi _{k}^{2}} is a special case of the gamma distribution and the univariate Wishart distribution. Specifically

    Chi-squared distribution

    Chi-squared distribution

    Chi-squared_distribution

  • Chi distribution
  • Probability distribution

    variable and the origin. The chi distribution describes the positive square roots of a variable obeying a chi-squared distribution. If Z 1 , … , Z k {\displaystyle

    Chi distribution

    Chi distribution

    Chi_distribution

  • Noncentral chi-squared distribution
  • Noncentral generalization of the chi-squared distribution

    the noncentral chi-squared distribution (or noncentral chi-square distribution, noncentral χ 2 {\displaystyle \chi ^{2}} distribution) is a noncentral

    Noncentral chi-squared distribution

    Noncentral chi-squared distribution

    Noncentral_chi-squared_distribution

  • Chi-squared test
  • Statistical hypothesis test

    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

    Chi-squared test

    Chi-squared test

    Chi-squared_test

  • Inverse-chi-squared distribution
  • Probability distribution

    statistics, the inverse-chi-squared distribution (or inverted-chi-square distribution) is a continuous probability distribution of a positive-valued random

    Inverse-chi-squared distribution

    Inverse-chi-squared distribution

    Inverse-chi-squared_distribution

  • Generalized chi-squared distribution
  • Kind of probability distribution

    and statistics, the generalized chi-squared distribution (or generalized chi-square distribution) is the distribution of a quadratic function of a multinormal

    Generalized chi-squared distribution

    Generalized chi-squared distribution

    Generalized_chi-squared_distribution

  • Variance
  • Statistical measure of how far values spread from their average

    theorem shows that the unbiased sample variance S2 follows a scaled chi-squared distribution (see also: asymptotic properties and an elementary proof): ( n

    Variance

    Variance

    Variance

  • Pearson's chi-squared test
  • Evaluates how likely it is that any difference between data sets arose by chance

    Pearson's chi-squared test or Pearson's χ 2 {\displaystyle \chi ^{2}} test is a statistical test applied to sets of categorical data to evaluate how likely

    Pearson's chi-squared test

    Pearson's_chi-squared_test

  • Scaled inverse chi-squared distribution
  • Probability distribution

    of scaled inverse chi-squared distributions is linked to the inverse-chi-squared distribution and to the chi-squared distribution: If X ∼ ψ inv- χ 2

    Scaled inverse chi-squared distribution

    Scaled inverse chi-squared distribution

    Scaled_inverse_chi-squared_distribution

  • Proofs related to chi-squared distribution
  • characteristics related to the chi-squared distribution. Let random variable Y be defined as Y = X2 where X has normal distribution with mean 0 and variance

    Proofs related to chi-squared distribution

    Proofs_related_to_chi-squared_distribution

  • F-distribution
  • Continuous probability distribution

    since the chi-squared distribution is the sum of squares of independent standard normal random variables, the random variable of the F-distribution may also

    F-distribution

    F-distribution

    F-distribution

  • Hotelling's T-squared distribution
  • Type of probability distribution

    T-squared distribution (T2), proposed by Harold Hotelling, is a multivariate probability distribution that is tightly related to the F-distribution and

    Hotelling's T-squared distribution

    Hotelling's T-squared distribution

    Hotelling's_T-squared_distribution

  • Chi-square
  • Topics referred to by the same term

    The term chi-square, chi-squared, or χ 2 {\displaystyle \chi ^{2}} has various uses in statistics: chi-square distribution, a continuous probability distribution

    Chi-square

    Chi-square

  • Inverse-gamma distribution
  • Two-parameter family of continuous probability distributions

    parametrize the inverse gamma distribution differently, as a scaled inverse chi-squared distribution. The inverse gamma distribution's probability density function

    Inverse-gamma distribution

    Inverse-gamma distribution

    Inverse-gamma_distribution

  • Maxwell–Boltzmann distribution
  • Specific probability distribution function, important in physics

    the above chi-squared distribution with one degree of freedom, and the total energy will be distributed according to a chi-squared distribution with five

    Maxwell–Boltzmann distribution

    Maxwell–Boltzmann distribution

    Maxwell–Boltzmann_distribution

  • Wilks' theorem
  • Statistical theorem

    \infty } , the distribution of the test statistic − 2 log ⁡ ( Λ ) {\displaystyle -2\log(\Lambda )} asymptotically approaches the chi-squared ( χ 2 {\displaystyle

    Wilks' theorem

    Wilks'_theorem

  • List of probability distributions
  • Gamma distribution, and it is used in goodness-of-fit tests in statistics. The inverse-chi-squared distribution The noncentral chi-squared distribution The

    List of probability distributions

    List_of_probability_distributions

  • McNemar's test
  • Statistical test used on paired nominal data

    2 {\displaystyle \chi ^{2}} has a chi-squared distribution with 1 degree of freedom. If the χ 2 {\displaystyle \chi ^{2}} result is significant, this

    McNemar's test

    McNemar's_test

  • Erlang distribution
  • Family of continuous probability distributions

    the distribution simplifies to the chi-squared distribution with 2k degrees of freedom. It can therefore be regarded as a generalized chi-squared distribution

    Erlang distribution

    Erlang distribution

    Erlang_distribution

  • Noncentral chi distribution
  • chi-squared distribution. Other related distributions may be seen there. If X {\displaystyle X} is chi distributed: X ∼ χ k {\displaystyle X\sim \chi

    Noncentral chi distribution

    Noncentral_chi_distribution

  • Jarque–Bera test
  • Normality test

    variance. If the data comes from a normal distribution, the JB statistic asymptotically has a chi-squared distribution with two degrees of freedom, so the statistic

    Jarque–Bera test

    Jarque–Bera_test

  • Fluctuation loss
  • Interference effect in radar systems

    number of individual radiators and considering the result using the chi-squared distribution: p ( σ ) = m Γ ( m ) σ a v ( m σ σ a v ) m − 1 e − m σ σ a v I

    Fluctuation loss

    Fluctuation_loss

  • Relationships among probability distributions
  • Topic in probability theory and statistics

    gamma distribution with shape parameter α = v/2 and rate parameter β = 1/2 is a chi-squared distribution with ν degrees of freedom. A chi-squared distribution

    Relationships among probability distributions

    Relationships among probability distributions

    Relationships_among_probability_distributions

  • Noncentral F-distribution
  • Probability distribution generalizing the F-distribution with a noncentrality parameter

    F-distribution. It describes the distribution of the quotient (X/n1)/(Y/n2), where the numerator X has a noncentral chi-squared distribution with n1 degrees of freedom

    Noncentral F-distribution

    Noncentral_F-distribution

  • Beta distribution
  • Probability distribution

    it is apparent from the fact that for the chi-squared distribution the excess kurtosis is 12/k and the square of the skewness is 8/k, hence (excess kurtosis

    Beta distribution

    Beta distribution

    Beta_distribution

  • Chi (letter)
  • Twenty-second letter of the Greek alphabet

    various uses, including the chi-squared distribution, the chi-squared test, and chi-squared target model In algebraic topology, Chi is used to represent the

    Chi (letter)

    Chi_(letter)

  • Rice distribution
  • Probability distribution

    ^{2}}{2\sigma ^{2}}}} ⁠. Generate X {\displaystyle X} having a chi-squared distribution with ⁠ 2 P + 2 {\displaystyle 2P+2} ⁠ degrees of freedom. Set R

    Rice distribution

    Rice distribution

    Rice_distribution

  • Wishart distribution
  • Generalization of gamma distribution to multiple dimensions

    Wishart distribution. Chi-squared distribution Complex Wishart distribution F-distribution Gamma distribution Hotelling's T-squared distribution Inverse-Wishart

    Wishart distribution

    Wishart_distribution

  • Exponential distribution
  • Probability distribution

    \operatorname {K} (\alpha ,\beta )} (K-distribution) If also λ = 1/2 then X ∼ χ2 2; i.e., X has a chi-squared distribution with 2 degrees of freedom. Hence:

    Exponential distribution

    Exponential distribution

    Exponential_distribution

  • Gamma distribution
  • Probability distribution

    distribution, Erlang distribution, and chi-squared distribution are special cases of the gamma distribution. There are two equivalent parameterizations

    Gamma distribution

    Gamma distribution

    Gamma_distribution

  • Yates's correction for continuity
  • Statistical method

    correction modifies the standard chi-squared test to account for the fact that a continuous distribution (chi-squared) is used to approximate discrete

    Yates's correction for continuity

    Yates's_correction_for_continuity

  • Student's t-distribution
  • Probability distribution

    has a chi-squared distribution (χ2-distribution) with ν {\displaystyle \nu } degrees of freedom; Z and V are independent; A different distribution is defined

    Student's t-distribution

    Student's t-distribution

    Student's_t-distribution

  • White test
  • Statistical test

    LM = n R 2 . {\displaystyle {\text{LM}}=nR^{2}.} This follows a chi-squared distribution, with degrees of freedom equal to P − 1, where P is the number

    White test

    White_test

  • Log-normal distribution
  • Probability distribution

    follows a normal distribution, and that both S 1 2 {\displaystyle S_{1}^{2}} and S 2 2 {\displaystyle S_{2}^{2}} has a chi-squared distribution, which is approximately

    Log-normal distribution

    Log-normal distribution

    Log-normal_distribution

  • Fisher's method
  • Statistical method

    fact can be used to determine the p-value for X2. The distribution of X2 is a chi-squared distribution for the following reason; under the null hypothesis

    Fisher's method

    Fisher's method

    Fisher's_method

  • Posterior predictive distribution
  • Distribution of new data marginalized over the posterior

    prior scaled-inverse-chi-squared distribution placed on σx2, with hyperparameters ν and σ2. The resulting compound distribution t ( x | μ , ν , σ 2 )

    Posterior predictive distribution

    Posterior_predictive_distribution

  • Normal distribution
  • Probability distribution

    {\textstyle |X-\mu |/\sigma \sim \chi _{1}} . The square of X / σ {\textstyle X/\sigma } has the noncentral chi-squared distribution with one degree of freedom:

    Normal distribution

    Normal distribution

    Normal_distribution

  • Gini coefficient
  • Measure of inequality of a statistical distribution

    November 2022. "Chi-Squared Distribution -- from Wolfram MathWorld". mathworld.wolfram.com. Retrieved 11 January 2023. "Weibull Distribution: Characteristics

    Gini coefficient

    Gini coefficient

    Gini_coefficient

  • Complex normal distribution
  • Statistical distribution of complex random variables

    distribution (a complex normal distribution is a bivariate normal distribution) Generalized chi-squared distribution Wishart distribution Complex random variable

    Complex normal distribution

    Complex_normal_distribution

  • Quadratic form (statistics)
  • Vector in statistics

    addition, a quadratic form such as this follows a generalized chi-squared distribution. The case for general Λ {\displaystyle \Lambda } can be derived

    Quadratic form (statistics)

    Quadratic_form_(statistics)

  • Poisson distribution
  • Discrete probability distribution

    Poisson distribution can be expressed using the relationship between the cumulative distribution functions of the Poisson and chi-squared distributions. The

    Poisson distribution

    Poisson distribution

    Poisson_distribution

  • Residual sum of squares
  • Statistical measure of the discrepancy between data and an estimation model

    sum of squares (RSS), also known as the sum of squared residuals (SSR) or the sum of squared estimate of errors (SSE), is the sum of the squares of residuals

    Residual sum of squares

    Residual_sum_of_squares

  • Reduced chi-squared statistic
  • Test statistic

    ^{2}}{\nu }},} where the chi-squared is a weighted sum of squared deviations: χ 2 = ∑ i ( O i − C i ) 2 σ i 2 {\displaystyle \chi ^{2}=\sum _{i}{\frac

    Reduced chi-squared statistic

    Reduced_chi-squared_statistic

  • Rayleigh distribution
  • Probability distribution

    Rayleigh distribution is a continuous probability distribution for nonnegative-valued random variables. Up to rescaling, it coincides with the chi distribution

    Rayleigh distribution

    Rayleigh distribution

    Rayleigh_distribution

  • Multinomial distribution
  • Generalization of the binomial distribution

    converges in distribution to the chi-squared distribution χ 2 ( k − 1 ) {\displaystyle \chi ^{2}(k-1)} . [Proof] The space of all distributions over categories

    Multinomial distribution

    Multinomial_distribution

  • Hosmer–Lemeshow test
  • Statistical test for logistic regression models

    the p-value Compare the computed Hosmer–Lemeshow statistic to a chi-squared distribution with Q − 2 degrees of freedom to calculate the p-value. There are

    Hosmer–Lemeshow test

    Hosmer–Lemeshow_test

  • Noncentral distribution
  • (central) chi-squared distribution is the distribution of a sum of squared independent standard normal distributions, i.e., normal distributions with mean

    Noncentral distribution

    Noncentral_distribution

  • Curse of dimensionality
  • Difficulties arising when analyzing data with many aspects ("dimensions")

    . This also helps to understand the chi-squared distribution. Indeed, the (non-central) chi-squared distribution associated to a random point in the interval

    Curse of dimensionality

    Curse_of_dimensionality

  • Errors and residuals
  • Statistics concept

    r_{i}=X_{i}-{\overline {X}}.} The sum of squares of the statistical errors, divided by σ2, has a chi-squared distribution with n degrees of freedom: 1 σ 2 ∑

    Errors and residuals

    Errors_and_residuals

  • Degrees of freedom (statistics)
  • Number of values in the final calculation of a statistic that are free to vary

    with the squared lengths (or "sum of squares" of the coordinates) of such vectors, and the parameters of chi-squared and other distributions that arise

    Degrees of freedom (statistics)

    Degrees_of_freedom_(statistics)

  • Welch–Satterthwaite equation
  • Equation to approximate pooled degrees of freedom

    probability distribution of χ' cannot be expressed analytically. However, its distribution can be approximated by another chi-squared distribution, whose effective

    Welch–Satterthwaite equation

    Welch–Satterthwaite_equation

  • Lack-of-fit sum of squares
  • Value in statistics

    of squares due to pure error, divided by the error variance σ2, has a chi-squared distribution with N − n degrees of freedom; The sum of squares due

    Lack-of-fit sum of squares

    Lack-of-fit_sum_of_squares

  • Multivariate normal distribution
  • Generalization of the one-dimensional normal distribution to higher dimensions

    p ) {\displaystyle \chi _{k}^{2}(p)} is the quantile function for probability p {\displaystyle p} of the chi-squared distribution with k {\displaystyle

    Multivariate normal distribution

    Multivariate normal distribution

    Multivariate_normal_distribution

  • Generalized integer gamma distribution
  • special case of the generalized chi-squared distribution. A related concept is the generalized near-integer gamma distribution (GNIG). The random variable

    Generalized integer gamma distribution

    Generalized_integer_gamma_distribution

  • P-value
  • Function of the observed sample results

    his Pearson's chi-squared test, using the chi-squared distribution and notated as capital P. The p-values for the chi-squared distribution (for various

    P-value

    P-value

  • Mahalanobis distance
  • Statistical distance measure

    dimensions other than 2, the cumulative chi-squared distribution should be consulted. In a normal distribution, the region where the Mahalanobis distance

    Mahalanobis distance

    Mahalanobis_distance

  • Sensitivity index
  • Statistic used in signal detection theory

    0}^{2}>0\right)} ( χ ~ 2 {\displaystyle {\tilde {\chi }}^{2}} denotes the generalized chi-squared distribution), where w = [ σ s 2 − σ n 2 ] , k = [ 1 1 ]

    Sensitivity index

    Sensitivity_index

  • Standard normal deviate
  • Normally distributed deviate

    other marginal distributions may involve manipulating sequences of standard normal deviates: an example here is the chi-squared distribution, random values

    Standard normal deviate

    Standard_normal_deviate

  • Ordinary least squares
  • Method for estimating the unknown parameters in a linear regression model

    proportional to the chi-squared distribution: s 2   ∼   σ 2 n − p ⋅ χ n − p 2 {\displaystyle s^{2}\ \sim \ {\frac {\sigma ^{2}}{n-p}}\cdot \chi _{n-p}^{2}} The

    Ordinary least squares

    Ordinary least squares

    Ordinary_least_squares

  • G-test
  • Statistical test

    G} is asymptotically chi-squared distributed as the total number of observations tends to infinity (convergence in distribution). Furthermore, the total

    G-test

    G-test

  • Analysis of variance
  • Collection of statistical models

    components (that for error) specifies a chi-squared distribution which describes the associated sum of squares, while the same is true for "treatments"

    Analysis of variance

    Analysis_of_variance

  • List of statistics articles
  • inequality Chernoff face Chernoff's distribution Chernoff's inequality Chi distribution Chi-squared distribution Chi-squared test Chinese restaurant process

    List of statistics articles

    List_of_statistics_articles

  • Goodness of fit
  • Metric for fit of statistical models

    determination (the R-squared measure of goodness of fit); Lack-of-fit sum of squares; Mallows's Cp criterion Prediction error Reduced chi-square The following

    Goodness of fit

    Goodness_of_fit

  • Box–Muller transform
  • Statistical transform

    \,} Because R2 is the square of the norm of the standard bivariate normal variable (X, Y), it has the chi-squared distribution with two degrees of freedom

    Box–Muller transform

    Box–Muller transform

    Box–Muller_transform

  • Benford's law
  • Observation that in many real-life datasets, the leading digit is likely to be small

    F-distribution is fitted well for low degrees of freedom. With increasing dfs the fit decreases but much more slowly than the chi-squared distribution.

    Benford's law

    Benford's law

    Benford's_law

  • Multinomial test
  • ~N~} increases, the distribution of   − 2 ln ⁡ ( [ L R ] )   {\displaystyle ~-2\ln([{\mathcal {LR}}])~} converges to that of chi-squared with   k − 1   {\displaystyle

    Multinomial test

    Multinomial_test

  • Wilks's lambda distribution
  • Probability distribution used in multivariate hypothesis testing

    2(m-p+1)}.} Chi-squared distribution Dirichlet distribution F-distribution Gamma distribution Hotelling's T-squared distribution Student's t-distribution Wishart

    Wilks's lambda distribution

    Wilks's_lambda_distribution

  • Laplace distribution
  • Probability distribution

    {\displaystyle 2}{b}}\sum _{i=1}^{n}|X_{i}-\mu |\sim \chi ^{2}(2n)} (chi-squared distribution). If X , Y ∼ Laplace ( μ , b ) {\displaystyle X,Y\sim {\textrm

    Laplace distribution

    Laplace distribution

    Laplace_distribution

  • Pearson distribution
  • Family of continuous probability distributions

    {Gamma} (m+1,b_{1}^{2})} . The Pearson type III distribution is a gamma distribution or chi-squared distribution. Defining new parameters: C 1 = b 1 2 b 2

    Pearson distribution

    Pearson distribution

    Pearson_distribution

  • Zero degrees of freedom
  • non-central chi-squared distribution with zero degrees of freedom can be used in testing the null hypothesis that a sample is from a uniform distribution on the

    Zero degrees of freedom

    Zero_degrees_of_freedom

  • Ratio distribution
  • Probability distribution

    by an independent chi-distributed random variable, while the F-distribution originates from the ratio of two independent chi-squared distributed random

    Ratio distribution

    Ratio_distribution

  • One- and two-tailed tests
  • Ways of computing statistical significance

    One-tailed tests are used for asymmetric distributions that have a single tail, such as the chi-squared distribution, which are common in measuring goodness-of-fit

    One- and two-tailed tests

    One- and two-tailed tests

    One-_and_two-tailed_tests

  • Logistic regression
  • Statistical model for a binary dependent variable

    }}_{\varphi })=11.6661\ldots } Using the chi-squared test of significance, the integral of the chi-squared distribution with one degree of freedom from 11.6661

    Logistic regression

    Logistic regression

    Logistic_regression

  • Cochran's theorem
  • Statistical theorem in the analysis of variance

    r_{1}+\cdots +r_{k}=N} , the Qi are independent each Qi has a chi-squared distribution with ri degrees of freedom. Often it's stated as ∑ i A i = A {\displaystyle

    Cochran's theorem

    Cochran's_theorem

  • Lévy distribution
  • Probability distribution

    {\displaystyle X\,\sim \,\operatorname {Scale-inv-\chi ^{2}} (1,c)} (scaled-inverse-chi-squared distribution). If X ∼ Levy ⁡ ( μ , c ) {\displaystyle X\sim

    Lévy distribution

    Lévy distribution

    Lévy_distribution

  • Random variable
  • Variable representing a random phenomenon

    This is a chi-squared distribution with one degree of freedom. Suppose X {\displaystyle X} is a random variable with a normal distribution, whose density

    Random variable

    Random variable

    Random_variable

  • Homoscedasticity and heteroscedasticity
  • Statistical property

    for a chi-squared distribution with the degrees of freedom equal to the number of independent variables. The null hypothesis of this chi-squared test is

    Homoscedasticity and heteroscedasticity

    Homoscedasticity and heteroscedasticity

    Homoscedasticity_and_heteroscedasticity

  • 97.5th percentile point
  • Number useful in statistics for analyzing a normal curve

    975}}e^{-x^{2}/2}\,\mathrm {d} x=0.95.} Its square, about 3.84146, is the 95th percentile point of a chi-squared distribution with 1 degree of freedom, often used

    97.5th percentile point

    97.5th percentile point

    97.5th_percentile_point

  • Probability distribution
  • Mathematical function for the probability a given outcome occurs in an experiment

    chi-squared test) Student's t distribution, the distribution of the ratio of a standard normal variable and the square root of a scaled chi squared variable;

    Probability distribution

    Probability distribution

    Probability_distribution

  • Mathematical statistics
  • Branch of statistics

    chi-squared test) Student's t distribution, the distribution of the ratio of a standard normal variable and the square root of a scaled chi squared variable;

    Mathematical statistics

    Mathematical statistics

    Mathematical_statistics

  • Generalised hyperbolic distribution
  • Continuous probability distribution

    {\text{?}},{\text{?}},{\text{?}},{\text{?}})\,} normal-inverse chi-squared distribution G H ( ? , ? , ? , ? , ? ) {\displaystyle \mathrm {GH} ({\text{

    Generalised hyperbolic distribution

    Generalised_hyperbolic_distribution

  • Hardy–Weinberg principle
  • Principle in genetics

    classes. If this is the case, then the asymptotic assumption of the chi-squared distribution, will no longer hold, and it may be necessary to use a form of

    Hardy–Weinberg principle

    Hardy–Weinberg principle

    Hardy–Weinberg_principle

  • Minimum chi-square estimation
  • population distribution if a specified test statistic is too large, when that statistic would have approximately a chi-square distribution if the null

    Minimum chi-square estimation

    Minimum_chi-square_estimation

  • Distribution of the product of two random variables
  • Probability distribution

    \;\;{\text{ as }}\rho \rightarrow 1\\\end{aligned}}} which is a Chi-squared distribution with one degree of freedom. Multiple correlated samples. Nadarajaha

    Distribution of the product of two random variables

    Distribution_of_the_product_of_two_random_variables

  • Levene's test
  • Statistical test of equal group variances

    Cauchy distribution (a heavy-tailed distribution) and the median performed best when the underlying data followed a chi-squared distribution with four

    Levene's test

    Levene's_test

  • Gary Robinson
  • American software engineer and mathematician

    approach. Gary Robinson's Linux Journal article discussed using the chi squared distribution." Ben Kamens, Fog Creek Publishing, Bayesian Filtering: Beyond

    Gary Robinson

    Gary Robinson

    Gary_Robinson

  • Chi-square automatic interaction detection
  • Decision tree learning technique

    that it is non-parametric.[citation needed] Bonferroni correction Chi-squared distribution Decision tree learning Latent class model Market segment Multiple

    Chi-square automatic interaction detection

    Chi-square_automatic_interaction_detection

  • Misconceptions about the normal distribution
  •  278. ISBN 978-1-420-01137-1. Notes More precisely 1.53817..., the square root of the median of a chi-squared distribution with 3 degrees of freedom.

    Misconceptions about the normal distribution

    Misconceptions_about_the_normal_distribution

  • X2
  • Topics referred to by the same term

    Mountain Chi-squared distribution, a theoretical probability distribution in inferential statistics Square (algebra), also known as the algebraic square Keyboard

    X2

    X2

  • Multiplicative noise
  • Signal processing phenomenon

    by generating a random variable from the appropriate noncentral chi-squared distribution. The Heston model is a stochastic volatility model used in mathematical

    Multiplicative noise

    Multiplicative_noise

  • Kruskal–Wallis test
  • Non-parametric method for testing whether samples originate from the same distribution

    distribution of H {\displaystyle H} can be quite different from this chi-squared distribution. If a table of the chi-squared probability distribution

    Kruskal–Wallis test

    Kruskal–Wallis test

    Kruskal–Wallis_test

  • Fisher's exact test
  • Statistical significance test

    the sampling distribution of the test statistic that is calculated is only approximately equal to the theoretical chi-squared distribution. The approximation

    Fisher's exact test

    Fisher's_exact_test

  • Unimodality
  • Property of having a unique mode or maximum value

    normal distributions, which are unimodal. Other examples of unimodal distributions include Cauchy distribution, Student's t-distribution, chi-squared distribution

    Unimodality

    Unimodality

  • Johnson–Lindenstrauss lemma
  • Mathematical result

    is chi-square distributed, that is, r ∼ χ 2 ( k ) {\textstyle r\sim \chi ^{2}(k)} . Thus, it satisfies a concentration inequality for the chi-squared distribution:

    Johnson–Lindenstrauss lemma

    Johnson–Lindenstrauss_lemma

  • Cochran's Q test
  • Statistical test

    − 1 2 {\displaystyle T>\chi _{1-\alpha ,k-1}^{2}} where Χ21 − α,k − 1 is the (1 − α)-quantile of the chi-squared distribution with k − 1 degrees of freedom

    Cochran's Q test

    Cochran's_Q_test

  • Mean squared error
  • Measure of the error of an estimator

    In statistics, the mean squared error (MSE) or mean squared deviation (MSD) of an estimator (of a procedure for estimating an unobserved quantity) measures

    Mean squared error

    Mean_squared_error

  • Cox–Ingersoll–Ross model
  • Stochastic model for the evolution of financial interest rates

    c={\frac {2a}{(1-e^{-aT})\sigma ^{2}}}} , and Y is a non-central chi-squared distribution with 4 a b σ 2 {\displaystyle {\frac {4ab}{\sigma ^{2}}}} degrees

    Cox–Ingersoll–Ross model

    Cox–Ingersoll–Ross model

    Cox–Ingersoll–Ross_model

  • Effect size
  • Statistical measure of the magnitude of a phenomenon

    square root of the chi-squared statistic divided by the sample size. Similarly, Cramér's V is computed by taking the square root of the chi-squared statistic

    Effect size

    Effect_size

  • Euler's constant
  • Difference between logarithm and harmonic series

    the Weibull and Lévy distributions, and, implicitly, of the chi-squared distribution for one or two degrees of freedom. An upper bound on Shannon entropy

    Euler's constant

    Euler's constant

    Euler's_constant

  • Relative likelihood
  • Statistical model tool

    log-likelihoods and the probability distribution of the test statistic is approximately a chi-squared distribution with degrees-of-freedom (df) equal to

    Relative likelihood

    Relative_likelihood

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  • Squarely
  • adv.

    In a square form or manner.

  • Sugared
  • a.

    Also used figuratively; as, sugared kisses.

  • Squarer
  • n.

    One who, or that which, squares.

  • Square
  • n.

    A square piece or fragment.

  • Squier
  • n.

    A square. See 1st Squire.

  • Quadratic
  • a.

    Of or pertaining to a square, or to squares; resembling a quadrate, or square; square.

  • Square
  • a.

    Rendering equal justice; exact; fair; honest, as square dealing.

  • Square
  • n.

    An instrument having at least one right angle and two or more straight edges, used to lay out or test square work. It is of several forms, as the T square, the carpenter's square, the try-square., etc.

  • Square
  • a.

    Even; leaving no balance; as, to make or leave the accounts square.

  • Squared
  • imp. & p. p.

    of Square

  • Square
  • n.

    To multiply by itself; as, to square a number or a quantity.

  • Square
  • n.

    Hence, anything which is square, or nearly so

  • Squire
  • n.

    A square; a measure; a rule.

  • Square
  • n.

    The product of a number or quantity multiplied by itself; thus, 64 is the square of 8, for 8 / 8 = 64; the square of a + b is a2 + 2ab + b2.

  • Square
  • a.

    Forming a right angle; as, a square corner.

  • Squarer
  • n.

    One who squares, or quarrels; a hot-headed, contentious fellow.

  • squired
  • imp. & p. p.

    of Squire

  • Square
  • n.

    To place at right angles with the keel; as, to square the yards.

  • Square
  • a.

    Having four equal sides and four right angles; as, a square figure.

  • Square-toed
  • n.

    Having the toe square.