Books on probability and statistics
Below we indicate some useful books. We suggest to see Amazon for further comments to decide which book best suites you.
A simple introduction to probability and statistics for a broad audience, with gentle mathematical use
Sanjeev Kulkarni, Gilbert Harman: "An Elementary Introduction to Statistical Learning Theory"
Recommended by many, from Stanford
Hastie, Tibshirani, Friedman: "The Elements of Statistical Learning"
Nice book covering much of the statistics and probability used in machine learning books
Larry Wassermann: "All of Statistics: A Concise Course in Statistical Inference"
Another book suggested by others
Dimitri P. Bertsekas, John N. Tsitsiklis "Introduction to Probability, 2nd Editionby"
WEB Resources on Statistics
A Brief Introduction to Graphical Models and Bayesian Networks (By Kevin Murphy, 1998; web-page with tutorial and other resources)
http://people.cs.ubc.ca/~murphyk/Bayes/bnintro.html
Bayes Net Toolbox for Matlab (Written by Kevin Murphy, 1997--2002. Last updated: 19 October 2007)
https://code.google.com/p/bnt/
Online free course on statistics and probability
Stanford's Probability and Statistics
Course with no deadlines self-paced course, no statement of accomplishment, free of cost, no credit, no verification, world class material:
http://online.stanford.edu/course/probability-and-statistics-self-paced
A coursera course focussed on R
Course on statistic and probability, focussed on R, one of the most important software for statistical analysis become a standard in scintific research (it is also open-source):
Duke U., Statistics with R:
https://www.coursera.org/specializations/statistics
Statistics applied to neuroscience
Statistical Parametric Mapping (and Dynamic Causal Modelling; by University College London):
http://www.fil.ion.ucl.ac.uk/spm/