The XSQ_TEST function computes the Chi-square goodness-of-fit test between observed frequencies and the expected frequencies of a theoretical distribution. The result is a two-element vector containing the Chi-square test statistic X2 and the one-tailed probability of obtaining a value of X2 or greater.
Expected frequencies of magnitude less than 5 are combined with adjacent elements resulting in a reduction of cells used to formulate the chi-squared test statistic. If the observed frequencies differ significantly from the expected frequencies, the Chi-square test statistic will be large and the fit is poor. This situation requires the rejection of the hypothesis that the given observed frequencies are an accurate approximation to the expected frequency distribution.
This routine is written in the IDL language. Its source code can be found in the file
subdirectory of the IDL distribution.
Set this keyword to a named variable that will contain a vector of expected frequencies used to formulate the Chi-square test statistic. If each of the expected frequencies contained in Exfreq , has a magnitude of 5 or greater, then this vector is identical to Exfreq . If Exfreq contains elements of magnitude less than 5, adjacent expected frequencies are combined. The identical combinations are performed on the corresponding elements of Obfreq .
Set this keyword to a named variable that will contain a vector of observed frequencies used to formulate the Chi-square test statistic. The elements of this vector are often referred to as the "cells" of the observed frequencies. The length of this vector is determined by the length of EXCELL described below.
Since the vector of expected frequencies contains elements of magnitude less than 5, adjacent expected frequencies are combined resulting in fewer cells. The identical combinations are performed on the corresponding elements of observed frequencies. The computed value of 0.383920 indicates that there is no reason to reject the proposed hypothesis at the 0.05 significance level.