Binary discriminant analysis (BDA) is a readily understood, easily used technique for identifying binary variables and their common trends which are most important for discriminating between groups. For the plant ecologist, the technique can be used on species lists to reveal similar patterns of preference or avoidance among species responding significantly to a multistate environmental parameter such as soil type, rock type, or aspect. In Q—mode BDA, orthogonal canonical factors are obtained which represent uncorrelated floristic trends best separating the groups. Scores of species on the factors can be plotted in multidimensional hyperspace, showing how each species responds to the floristic trends. In R—mode BDA, groups of species with similar responds to the environmental parameter are identified. These groups may be interpreted as statistical associations or community components comprised of species with similar ecologies. An example using lists of woody species from the Maryland Piedmont and Coastal Plain sorted according to underlying rock type produces floristic trends which are easily interpreted and species groups which are readily understandable.