Pedagogy of chi‐square goodness of fit test for continuous distributions

Chi‐square goodness of fit testing to examine whether or not it is reasonable to assume that a random sample of the data comes from a specific probability density was one of the topics covered in an undergraduate engineering probability course. In the absence of details on this topic in engineering probability books, a Matlab® demo was created to facilitate the link between theory and practice. The step‐by‐step procedure to determine the closest fit among a number of continuous densities has been demonstrated involving binning (fixed width and fixed population), parameter estimation, and computation of the test statistic, degrees of freedom and the P values. The cautionary aspects of the test regarding the variability in test results have been illustrated by choosing a smaller size data through permutation. The pedagogical aspects of procedure demonstrated suggest that it may be used to fill the gaps in textbooks devoted to probability and statistics.