Merge branch 'master' of github.com:UBC-STAT/stat-301

docs/index-page.md

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 ### Course Description
 
-Data analysis using statistical models and algorithms (e.g., linear and logistic regression, peeking, bandit, and variable selection algorithms) in case studies from different disciplines. Generative versus out-of-sample predictive models. Reproducible and transparent workflows for computer scripts and reports.
+Data analysis using statistical models and algorithms (e.g., linear and logistic regression, peeking, bandit, and variable selection algorithms) in case studies from different disciplines. Generative versus out-of-sample predictive models. Reproducible and transparent workflows for computer scripts and reports. Class notes by Gabriela Cohen Freue can be found [here](https://ubc-stat.github.io/stat301book/intro.html)
+
+

docs/schedule-page.md

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 ## Schedule
 
+Class notes can be found [here](https://ubc-stat.github.io/stat301book/intro.html)
+
 <table id="course-schedule">
     <caption>Table 1: Course Calendar</caption>
     <thead>

docs/syllabus-page.md

@@ -46,6 +46,8 @@ Times are in Pacific Time
 
 ### Textbooks
 
+- Class notes by Gabriela Cohen Freue can be found [here](https://ubc-stat.github.io/stat301book/intro.html)
+
 - James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning: With applications in R. 
   - Available ONLINE at UBC Library: http://resolve.library.ubc.ca/cgi-bin/catsearch?bid=6667014
 - Rafael Irizarry. Introduction to Data Science.