Introduction
Reason #3: RStudio’s shiny
Examples
“Slow” Simulation
Understanding Model Assumptions
Types of Error
Illustrating Fine Points
Playing Games

Now that we have reached the milestone of 30,000 (!) enthusiastic R students, and the DataCamp platform is paving its way into academics and professional organizations, we felt it was time to take our design to a higher level. So as of this week, your favourite free learning platform for R tutorials and data science will have a totally new look and feel!

DataCamp first to offer free interactive R tutorials via the OpenIntro platform. In one week, the ten-week Coursera course on Data Analysis and Statistical Inference by prof. Mine Çetinkaya-Rundel of Duke University comes to an end. At DataCamp it was one of our first experiences providing interactive R exercises on a large scale, and we’re proud to say

(Generalized) Linear models make some strong assumptions concerning the data structure: Independance of each data points Correct distribution of the residuals Correct specification of the variance structure Linear relationship between the response and the linear predictor For simple lm 2-4) means that the residuals should be normally distributed, the variance should be homogenous across the

e-mails with the latest R posts.

(You will not see this message again.)