# Chapter 1 Introduction

These (still incomplete) lecture notes should help you get familiar with ANOVA and R. From a methodological point of view, we mostly follow the book of . We try to apply most methods directly in R. This means you will see a lot of both R code and R output having the following form.

text <- "Let's get started ..."
paste(text, "now!", sep = " ")
## [1] "Let's get started ... now!"

If you are completely new to R you can get an overview of online courses here: https://education.rstudio.com/.

We expect that you have already attended an introductory course to probability and statistics covering the basic concepts of statistical inference (estimation, hypothesis tests, confidence intervals) up to the two-sample $$t$$-test.

If you find any errors, inconsistencies or if you miss something in these lecture notes, please e-mail me at meier@stat.math.ethz.ch or fill out the form anonymously at https://goo.gl/ZBvjj9.