Chi-square test

From HandWiki


If N measurements yi are compared to some model or theory predicting values gi, and if the measurements are assumed normally distributed around gi, uncorrelated and with variances Hepa img120.gif , then the sum

Hepa img121.gif

follows the Hepa img111.gif (chi-square) distribution with N degrees of freedom. The Hepa img111.gif test compares s with the integral of the Hepa img111.gif distribution; if the sum above is equal to the quantile $ x_{\alpha}$ of the $ \chi^{2}$ distribution

Hepa img123.gif

then the probability of obtaining s or a larger value in the 'null hypothesis' (i.e. the yi are drawn from a distribution described by the $ g_i, \sigma^{2}_{i}$ ) is given by $ 1- \alpha$.

Integral curves for the Hepa img111.gif distribution exist in computer libraries or are tabulated in the literature. Note that the test may express little about the inherent assumptions; wrong hypotheses or measurements can, but need not cause large Hepa img111.gif 's. The only statement to make about a measured s is the one above: `` Hepa img124.gif is the probability of finding a Hepa img111.gif as large as s or larger, in the null hypothesis.

Rudolf K. Bock, Oct 2000