If your regression model contains a categorical predictor variable, you commonly test the significance of its categories against a preselected reference category. If all categories have (roughly) the same number of observations, you can also ...

If your regression model contains a categorical predictor variable, you commonly test the significance of its categories against a preselected reference category. If all categories have (roughly) the same number of observations, you can also ...

I was recently asked to do a panel of grouped boxplots of a continuous variable, with each panel representing a categorical grouping variable. This seems easy enough with ggplot2 and the facet_wrap function, but then my collaborator wanted p-values on the graphs! This post is my approach to the problem. First of all, one caveat. I’m a

This is the first chapter of our new web book, Raccoon - Statistical Models with R: it's an introduction to Linear models, with theoratical explanation and lots of examples + two summary tables with linear model formulae and functions in R The post Raccoon | Ch. 1 – Introduction to Linear Models with R appeared first on...

For those of us who received statistical training outside of statistics departments, it often emphasized procedures over principles. This entailed that we learned about various statistical techniques and how to perform analysis in a particular statistical software, but glossed over the mechanisms and mathematical statistics underlying these practices. While that training methodology (hereby referred to

Raccoon is a free web-book about Statistical Models with R. Raccoon is the collection of twenty years of notes, exercises and concepts working with statistics and R, and it is part of our web-book project, together with Rabbit: Introduction to R and Ramarro: R for Developers. The post Raccoon: Statistical Models with R free web-book appeared first on...

When we teach “R for statistics” to groups of scientists (who tend to be quite well informed in statistics, and just need a bit of help with R) we take the time to re-work some tests of model quality with the appropriate significance tests. We organize the lesson in terms of a larger and more … Continue...

I’m officially a Kaggler. Cut to the good ol’ Titanic challenge. Ol’ is right – It’s been running since 2012 and ends in 3 months! I showed up late to the party. Oh well, I guess it’s full steam ahead from now on. The competition ‘Machine Learning from Disaster’ asks you to apply machine learning to analyse and…

Dataset here. We are going to perform a linear mixed effects analysis of the relationship between height and treatment of trees, as studied over a period of time. Begin by reading in the data and making sure that the variables have the appropriate datatype. tree<- read.csv(path, header=T,sep=",") tree$ID<- factor(tree$ID) tree$plotnr <- factor(tree$plotnr) Plot the initial graph to…

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