Mala Mahadevan explains what ANOVA is and why it’s interesting:

ANOVA – or analysis of variance, is a term given to a set of statistical models that are used to analyze differences among groups and if the differences are statistically significant to arrive at any conclusion. The models were developed by statistician and evolutionary biologist Ronald Fischer. To give a very simplistic definition – ANOVA is an extension of the two way T-Test to multiple cases.

ANOVA is an older test and a fairly simple process, but is quite useful to understand.

Related Posts

Combining Plots In R With cowplot

Abdul Majed Raja shows how to use the cowplot library in R to merge together independent plots into a single image: The way it works in cowplot is that, we have assign our individual ggplot-plots as an R object (which is by default of type ggplot). These objects are finally used by cowplot to produce […]

Read More

Classifying Texts With Naive Bayes

I continue my series on Naive Bayes with another hand-calculation post: Step two is, on the surface, pretty tough: how do we figure out if a set of words is a business phrase or a baseball phrase? We could try to think up a set of features. For example, how long is the phrase? How many unique […]

Read More


October 2017
« Sep Nov »