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Introductory Material for Probability Theory
Introductory Material for Probability Theory
Jeffrey, R (2002) Subjective Probability: The real thing. An excellent text that sufficiently covers subjective probability and probability theory. Well worth your time to read so you understand basic probability theory.
Kroese, D.P. (2018) A Short Introduction to Probability. Another excellent primer on probability theory with some code examples (note: not R but looks very similar).
Gravner, J. (2011). Lecture Notes for Introductory Probability. A rather in-depth look at probability from Gravner's lectures at UC Davis.
Carnegie Mellon's probability and statistics (open and free) series
Introductory Material for R
Introductory Material for R
Black, K. (2015). R Tutorial. Kelly was generous enough to offer her introductory to R materials to the world. I found the notes to be extremely useful for most novices.
Learning R. LinkedIn Learning (login through GMU and link your linked in account).
Relevant Material for Python
Relevant Material for Python
New Python users ought to consult Allen's Think Python
Bayesian Articles and Books
Bayesian Articles and Books
My Google Drive collection of published articles.
Downey, A.B. Think Bayes. A book devoted to Bayesian thinking but code in Python. Well worth perusing - especially later in the semester when we try to run some models in Python.
Gelman, A. (2008). Objections to Bayesian statistics. Bayesian Analysis, 3(3), 445-449.
Rethinking Statistics Resources
Rethinking Statistics Resources
Richard McElreath's 2018-2019 GitHub repository for his course
Book website (Richard's personal) - see this site for all links associated with derivative efforts and complete text code from the book
AS Kurz effort to learn and port the code to more modern tools
Google Sites
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