Marhuenda García, YolandaMorales González, DomingoPardo Llorente, Julio ÁngelPardo Llorente, María del Carmen2023-06-202023-06-202005-030094-965510.1080/00949650410001687253https://hdl.handle.net/20.500.14352/50279The problem of testing if a given probability distribution fits to a set of independent and identically distributed observations is usually treated by categorizing the data range. Discretization can be done by means of relative frequencies or by using sample quantiles. In this article, quantile-based test statistics are proposed to test the hypothesis of uniformity in the interval (0, 1). Exact critical values of the family of Rukhin's statistics are estimated. A Monte Carlo simulation experiment is carried out to calculate powers of these tests in different alternatives. Results obtained from each kind of categorization are compared to give several recommendations about the use of Rukhin's statistics and type of categorization.journal articlehttp://www.tandfonline.com/doi/abs/10.1080/00949650410001687253http://www.tandfonline.commetadata only access519.22Testing goodness-of-fitThe family of Rukhin's statisticsOrder statisticsQuantilesSimulationEstadística matemática (Matemáticas)1209 Estadística