This page contains a few book and website references that will help you deepen your knowledge of the course material.
Fundamentals of Probability Theory and Statistics
There are many good introductory books on the basics of probability theory and statics - too many to list here. There also are good online resources, including videos by Khan Academy that may be very useful in the students’ preparation for exercises.
Statistics in Atmospheric Science
Wilks, D.S.: Statistical methods in the atmospheric sciences - 3rd ed. Academic Press, Oxford, 2011.
von Storch, H. and Zwiers, F.W.: Statistical Analysis in Climate Research. Cambridge University Press, Cambridge, 1999.
Sivia, D. S. and Skilling, J.: Data Analysis - A Bayesian Tutorial , Oxford University Press, 2006.
Neapolitan, R.E.: Learning Bayesian Networks - Prentice Hall, 2004.
The official Python 3 documentation includes tutorials that help you build on the basic Python skills you have learned in this course.
The Spyder documentation helps you get into the advanced features of the IDE.
The website of the matplotlib plotting library provides you with more example code for plotting with Python.