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

Naive Bays in R

Zulaikha Lateef takes us through the Naive Bayes algorithm and implementations in R: Naive Bayes is a Supervised Machine Learning algorithm based on the Bayes Theorem that is used to solve classification problems by following a probabilistic approach. It is based on the idea that the predictor variables in a Machine Learning model are independent of […]

Read More

Exporting Data from Power Query with R

Leila Etaati shows how you can use R to export data from Power Query to disk or to SQL Server: There is always a discussion on how to store back the data from Power BI to local computer or SQL Server Databases, in this short blog, I will show how to do it by writing […]

Read More


October 2017
« Sep Nov »