Normal nonparametric test for small samples of categorized variables

Paper aims Introduce a new statistical test to verify whether two small samples of variable classified into multiple categories are drawn from the same population. This problem can be represented by a contingency table of order (m x 2). Originality We do not have adequate asymptotic texts to treat this issue in all instantiation of the problem, and exact methods require substantial computational effort and specialized algorithms. The proposed test covers this gap. Research method It can be classified within design science research. The result, as well as the research process, meets the guidelines of that research method. Main findings Computational experiments show that the proposed test has similar effectiveness to the exact test, even when dealing with sparse data contingency tables and small values of m. Furthermore, examples show that it can work well in cases where the chi-square test, its numerous variations, and even in situation where the more recently developed methods fail. Implications for theory and practice This type of decision problem has received significant attention in the literature because it represents many real-life situations. The test proposed is as useful for small samples as Chi-square is for larger samples.