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1. An Introduction to Statistical Learning: with Applications in R

   23 Oct 2018 | Teaching Materials | Contributor(s):

   By Gareth James¹, Daniela Witten², Trevor Hastie³, Robert Tibshirani³

   1. University of Southern California 2. University of Washington 3. Stanford University

   This book provides an introduction to statistical learning methods and is aimed for upper level undergraduate students, masters students and Ph.D. students in the non-mathematical sciences.

   https://qubeshub.org/publications/847/?v=1

2. An Introduction to Statistical Learning: with Applications in R

   out of 5 stars 

   10 Jul 2015 | | Contributor(s):: Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani

   This resource has been updated - find the current version here:https://qubeshub.org/qubesresources/publications/847From the book website:This book provides an introduction to statistical learning methods. It is aimed for upper level undergraduate students,...

3. RESOURCES: Amazing course in statistical learning available freely on interwebs!

   09 Jul 2015 | Posted by Jeremy M Wojdak

   The authors of "An Introduction to Statistical Learning: with Applications in R", (Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani) have graciously made available a...

   https://qubeshub.org/news/blog/2015/07/amazing-course-in-statistical-learning-available-freely-on-interwebs

4. Clustering coefficients

   out of 5 stars 

   02 Jun 2015 | | Contributor(s):: Winfried Just, Hannah Lea Callender, Drew LaMar

   In this module we introduce several definitions of so-called clustering coefficients. A motivating example shows how these characteristics of the contact network may influence the spread of an infectious disease. In later sections we explore, both with the help of IONTW and theoretically,...

5. Small-world models

   out of 5 stars 

   02 Jun 2015 | | Contributor(s):: Winfried Just, Hannah Lea Callender

   Small-world networks are classes of networks that have both the small-world property and exhibit strong clustering. Two constructions of such networks are implemented in IONTW. Here we study, both theoretically and with simulation experiments, the structure of these networks and how it influences...