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Chi-Square Distribution Calculator

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Chi-Square Distribution: Definition, Formula, and Applications

Chi-Square Distribution

Definition: The chi-square distribution is a probability distribution of a sum of squared standard normal random variables. It is widely used in statistical inference, particularly for tests of independence and goodness-of-fit tests.

Formula:The probability density function (PDF) is given by: f(x;k)=12k/2Γ(k/2)xk/21ex/2,x>0f(x; k) = \frac{1}{2^{k/2}\Gamma(k/2)} x^{k/2-1}e^{-x/2}, \quad x > 0 Where: k=degrees of freedomk = \text{degrees of freedom} Γ(k/2)=gamma function\Gamma(k/2) = \text{gamma function}

Where:

  • kk is the degrees of freedom (shape parameter)
  • xx is the value of the chi-square statistic

Properties

  • Mean: E(X)=kE(X) = k (equals degrees of freedom)
  • Variance: Var(X)=2k\text{Var}(X) = 2k
  • Mode: max(k2,0)\max(k-2, 0)
  • Support: (0,)(0, \infty)
  • Special cases:
    • The sum of kk standard normal variables squared
    • χ12\chi^2_1 is the square of a standard normal
    • For large kk, approaches normal distribution

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