This page explains the one-way ANOVA test, which evaluates significant differences among group means based on variance. It requires five assumptions: normality of populations, independence of samples,...This page explains the one-way ANOVA test, which evaluates significant differences among group means based on variance. It requires five assumptions: normality of populations, independence of samples, equal variances, a categorical factor, and a numerical response. The null hypothesis posits that all group means are equal, while the alternative indicates at least one differs.
This page covers the F probability distribution and its applications in hypothesis testing, particularly in one-way ANOVA and variance testing. It highlights ANOVA's relevance across various fields li...This page covers the F probability distribution and its applications in hypothesis testing, particularly in one-way ANOVA and variance testing. It highlights ANOVA's relevance across various fields like psychology and business, introducing single factor ANOVA. The chapter provides an initial overview, with plans for more in-depth exploration in future courses, and is produced by OpenStax College for free access.
