The test for trends in proportions is also known as the Cochran Armitage test. It performs Chi-squared test for trend in proportions and is used to test whether there is a difference between groups considering the size of the groups. It takes count data from contingency tables where you have one nominal variable with two levels (i.e “Mutated”, “Wild-type”) and the other variable is an ordinal value with minimum 3 values where the variables is naturally ranked
The Chi-square test is used to compare differences between two or more categorical variables. All variables must be ordinal or nominal and summarized as a frequency table. It is a non-parametric test, meaning that it is suitable also for data that is not normally distributed. Some of the assumptions for performing a Chi-square test are: Each observation is independent of all the others (one observation per subject), and the categories must be mutually exclusive so that a subject fits into only one of the categories.
Disregarding the problematic side of Fisher, the statistical methods he developed are still very useful. Read any clinical paper, and I guarantee you that a Fisher exact test has been performed. Fisher-Exact is a statistical test used for 2x2 contingency tables of categorical data. It is particularity useful for small sample sizes where other tests, like the Chi square test would be unsuitable. Fisher-Exact from a 2x2 table: First you need to enter your data, and I will use some real life examples.