Chi-square test is an approximate test for large values of n. for the validity of chi square test of ‘goodness of fit’ between theory and experiment, the following conditions must be satisfied:

- The sample observations should be independent.
- Constraints on the cell frequencies, if any, should be linear, eg., ∑ni = ∑λi or ∑Oi = ∑Ei.
- N, the total frequency should be reasonably large, say, greater than 50.
- No theoretical cell frequency should be less than 5. Distribution is essentially a continuous distribution but it cannot maintain its character of continuity if cell frequency is less than5, then for the application of chi square test, it is pooled with the preceding or succeeding frequency so that the pooled frequency is more than 5 and finally adjust for the degrees of freedom lost in pooling.

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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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