In my book An Adventure in Statistics, the main character Zach goes on a reluctant adventure in his hometown of Elpis to find the missing love of his life, Alice. She is a brilliant scientists, and she has disappeared. Zach is a brilliant musician, but he knows nothing about science. Through his encounters with various characters he learns statistics. At a simple level it is a story about Zach searching for Alice, and seeking the truth, but it’s also about the unlikely friendship he develops with a sarcastic cat, it’s about him facing his fear of science and numbers, it’s about him learning to believe in himself. It’s a story about love, about not forgetting who you are. It’s about searching for the heartbeats that hide in the gaps between you and the people you love. It’s about having faith in others.
Like Zach, if you want to learn statistics you are going to have to go on an adventure through the districts of Elpis, finding out along the way how to analyse data. You will travel through five districts in turn:
1. Postverta is the first district, and it is bathed in the past. It is the old part of town, where Hallowed point and the repository impose themselves on the landscape. This district contains the foundations of statistics. There are three sections: the first looks at foundational statistical concepts such as fitting models and bias, as well as how to describe and present data; the second section looks at so-called nonparamatric tests; and the third looks at software options used on this website.
2. Antevorta looks to the future, and is the ultra-modern part of the city. Here you will learn about predicting variables that are continuous. You will take what you learnt about the general linear model, GLM in the Postverta district and develop it.
3. Porus is the rich district. This district is all about predicting a continuous outcome variable from categorical predictors. Many people tend to put these designs under a banner of ‘ANOVA’, but in fact they are all encapsulated by the general linear model. This section develops what you learned in the district to extend the general linear model, GLM to compare differences between means.
4. Egestes is the poor district. Here you will begin to look at predicting categorical outcome variables (rather than the continuous ones we have looked at in the other districts).
5. Veritas is the university district, where Alice works at the Beimeni Centre of Genetics. Here you will conclude your journey with an assortment of topics at the more advance end of the statistical spectrum.

Start Your Journey

First stop, Postverta