When data is collected from 2 binary variables on the same individuals or items, the data may be displayed as a 2 by 2 table. It is often of interest to determine whether there is some form of association between the two variables in the table, for example, comparing the % who test positive between two treatment groups, or between 2 subgroups such as males and females. The chi-square test is most commonly used by researchers to compare the percentage of individuals in two groups who share a trait.However, there are many other statistics that may be applied to a 2×2 table to provide more useful information and this course aims to help guide the researcher through alternative analyses to decide on the most appropriate investigation of their data.The following tests and concepts are covered in the course:Fishers exact testingAbsolute Risk Reduction (ARR)Proportions testsNumber needed to treat (NNT)Relative risk (RR)Attributable risk (AR)Odds ratio (OR)KappaSensitivity and specificityPositive and negative predictive valuesLikelihood ratiosFor each statistic we consider the interpretation and appropriate usages.