G-test

The G-test is a statistical method used to determine if observed data significantly differs from what we would expect under a specific hypothesis. It compares the actual counts or frequencies in categories to the expected counts, calculating a value called the G-statistic. If this value is large enough, it suggests that the differences are unlikely due to chance alone, indicating a meaningful discrepancy. The G-test is often used in fields like biology and social sciences to analyze categorical data, helping researchers assess whether observed patterns are statistically significant or just random variations.