A very powerful test for testing the significance of the discrepancy between theory and experiment was given by Prof. Karl Pearson in 1900 and is known as “Chi-Square test of goodness of fit”. It enables us to find if the deviation of the experiment from theory is just by chance or is it really due to the inadequacy of the theory to fit the observed data.

If Oi, (i= 1, 2,…, n) is a set of observed frequencies and Ei, (i= 1, 2,…, n) is the corresponding set of expected frequencies, then Karl Pearson’s chi-square, given by

Follows chi-square distribution with (n-1) degrees of freedom.

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- Exact Sampling distributions
- Derivation Of The Chi Square Distribution
- Moment Generating Function Of x
^{2}Distribution - Cumulant Generating Function Of x
^{2}Distribution - Limiting form of x
^{2}distribution for large degrees of freedom - Characteristic function of x
^{2}distribution: - Chi Square Probability Curve
- Conditions For The Validity Of Chi Square Test

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