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Chi-Square Curve

This article covers meaning & overview of Chi-Square Curve from statistical perspective.

Published by MBA Skool Team in Statistics Last Updated: January 26, 2024Read time:

What is Chi-Square Curve?

The distribution of the chi-square statistic is called the chi-square distribution. In a statistical experiment of a random sample of size n, having a standard deviation equal to σ, the standard deviation of the sample is equal to s.



A statistic, called chi-square, is defined using the following equation:


Χ^2 = [ ( n - 1 ) * s^2 ] / σ^2


If this experiment is repeated an infinite number of times, a sampling distribution for the chi-square statistic is obtained.


The chi-square distribution has the following properties:

  • The mean of the distribution is equal to the number of degrees of freedom: μ = v.
  • The variance is equal to two times the number of degrees of freedom: σ^2 = 2 * v
  • When the degrees of freedom are greater than or equal to 2, the maximum value for Y occurs when Χ^2 = v - 2.
  • As the degrees of freedom increase, the chi-square curve approaches a normal distribution.

This article has been researched & authored by the Business Concepts Team which comprises of MBA students, management professionals, and industry experts. It has been reviewed & published by the MBA Skool Team. The content on MBA Skool has been created for educational & academic purpose only.

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