useR! 2024

Goodness-of-fit remains a cornerstone in statistical analysis, with normality testing standing as a pivotal subset. With numerous solutions available, each boasting distinct characteristics in power, type I error control, and theoretical underpinnings, the landscape can be daunting to navigate. Moreover, the proliferation of R packages, encompassing both classical Fortran implementations and modern alternatives, adds another layer of complexity. In this presentation, we embark on a comprehensive journey through the normal goodness-of-fit tests. We will meticulously list, demonstrate, and critically assess these implementations, juxtaposing old-school methodologies with their contemporary counterparts. From the Shapiro-Wilk to the Anscombe-Glynn test, we'll explore a plethora of tests, shedding light on computacional performance, recent advancements and key differences in interface design.