Skip to content
Topics in Data Science
Branch: master
Clone or download
Pull request Compare This branch is even with jsrodriguezl:master.
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Type Name Latest commit message Commit time
Failed to load latest commit information.
Data Analysis for the Life Sciences
GitHub Session
Introduction to Statistical Learning 2016 Delete Week_1 Oct 10, 2018
Introduction to Statistical Learning 2018 6.2 Jan 16, 2019
MSMB updated - final Mar 20, 2019
Statistical-Rethinking @ c70aa8f Statistical Rethinking submodule Sep 29, 2018
The-Art-of-Data-Science @ 096f1bb
.gitignore exclude textbook Jun 20, 2017
.gitmodules Art of Data Science git submodule Sep 29, 2018

Table of Contents

Meeting details

Current activities

During March 13 - July 3 2019 we will be reading and doing exercises from Modern Statistics for Modern Biology by Susan Holmes and Wolfgang Huber. See the schedule wiki.

About us

This repository represent the joint effort of Paris Lodron University of Salzburg and the City University of New York Graduate School of Public Health and Health Policy. During active semesters we hold weekly meetings, where a chapter of a book is presented by a developing instructor with a focus on modern applied statistical methodology and using the R language. Our meetings are open to all (see details below), and materials we produce are licensed under the Creative Commons Attribution-ShareAlike 4.0 International Public License. We hope you find these materials useful and will join our sessions.

Getting started

  1. If you don't already have them, install R and RStudio following these instructions. Here is a short video showing how to use RStudio to contribute to this Github repo.

  2. Sign up for a GitHub account (also free) and clone this repository (open membership) in RStudio. Don't know what that means? Follow this tutorial. The process in RStudio is documented here or there is a video here.

  3. Leave a comment on the "Welcome" issue to let us know your GitHub username.

  4. Join our Google Group (open membership) and sign up to receive emails by visiting!forum/stat_learning.


  1. Pick the date or topic that best suits you and reserve it on the presentation schedule wiki, adding your GitHub username to the schedule table.

  2. Read the required section of the book, and do the associated exercises that you will present.

  3. Edit the presentation file using RStudio. All presentations should be authored using the .Rpres format, more infomation about the format is available here. Additionally, some previous presentation that can be used as examples are available here.

  4. Commit the presentation to GitHub from RStudio so that it is available to others. Don't know what that means? The process is documented here or there is a video here.

Past textbooks

Past textbooks have included:

You can’t perform that action at this time.