Probability, Statistics and Stochastic Processes
by Cosma Rohilla Shalizi
Number of pages: 71
Contents: Probability (Probability Calculus, Random Variables, Discrete and Continuous Distributions); Statistics (The Care and Handling of Data, Sampling, Estimation, Hypothesis Testing); Stochastic Processes (Sequences of Random Variables, Markov Processes, Continuous-Time Stochastic Processes).
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by O. Melchert - arXiv
In these lecture notes, a selection of frequently required statistical tools will be introduced and illustrated. They allow to post-process data that stem from, e.g., large-scale numerical simulations (aka sequence of random experiments).
by Allen B. Downey - Green Tea Press
Think Stats is an introduction to Probability and Statistics for Python programmers. This new book emphasizes simple techniques you can use to explore real data sets and answer interesting statistical questions. Basic skills in Python are assumed.
by Albert Tarantola - SIAM
The first part deals with discrete inverse problems with a finite number of parameters, while the second part deals with general inverse problems. The book for scientists and applied mathematicians facing the interpretation of experimental data.
by Marcus Kracht - UCLA
Contents: Basic Probability Theory (Conditional Probability, Random Variables, Limit Theorems); Elements of Statistics (Estimators, Tests, Distributions, Correlation and Covariance, Linear Regression, Markov Chains); Probabilistic Linguistics.