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R: Data Analysis and Visualization by Ágnes Vidovics-Dancs, Kata Váradi, Tamás Vadász, Ágnes Tuza, Balázs Árpád Szucs, Julia Molnár, Péter Medvegyev, Balázs Márkus, István Margitai, Péter Juhász, Dániel Havran, Gergely Gabler, Barbara Dömötör, Gergely Daróczi, Ádám Banai, Milán Badics, Ferenc Illés, Edina Berlinger, Bater Makhabel, Hrishi V. Mittal, Jaynal Abedin, Brett Lantz, Tony Fischetti

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What if my assumptions are unfounded?

The t-test and ANOVA are both considered parametric statistical tests. The word parametric is used in different contexts to signal different things but, essentially, it means that these tests make certain assumptions about the parameters of the population distributions from which the samples are drawn. When these assumptions are met (with varying degrees of tolerance to violation), the inferences are accurate, powerful (in the statistical sense), and are usually quick to calculate. When those parametric assumptions are violated, though, parametric tests can often lead to inaccurate results.

We've spoken about two main assumptions in this chapter: normality and homogeneity of variance. I mentioned that, even ...

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