In statistics, G-tests are likelihood-ratio or maximum likelihood statistical significance tests that are increasingly being used in situations where chi-squared tests were previously recommended.
The general formula for G is
where Oi is the observed frequency in a cell, E is the expected frequency on the null hypothesis, and the sum is taken over all cells, and where ln denotes the natural logarithm (log to the base e) and the sum is taken over all non-empty cells.
G-tests are coming into increasing use, particularly since they were recommended at least since the 1981 edition of the popular statistics textbook by Sokal and Rohlf.
Other related articles:
... Software for the R programming language (homepage here) to perform the G-test is available on a Professor's software page at the University of Alberta ... In SAS, one can conduct G-Test by applying the /chisq option in proc freq ... Fisher's G-Test in the GeneCycle Package of the R programming language (fisher.g.test) does not implement the G-test as described in this article, but rather Fisher's exact test of ...