Think Bayes - 2nd Edition
Allen B. Downey
Accessible introduction to Bayesian statistics using computational methods in Python. Covers Bayes theorem, distributions, estimation, hypothesis testing, ABC, decision analysis, and MCMC with practical examples.
Loading the book...
Keep reading
-
Next in this topic
An Introduction to Statistical Learning with Applications in PythonGold-standard introduction to statistical learning covering regression, classification, resampling, regularization, tree-based methods, SVMs, deep learning, and unsupervised learning with Python labs.
Verified PDF · Secure download - Introduction to Statistics
Comprehensive introduction covering descriptive statistics, probability, regression, and inferential methods. Public domain resource from Rice University with multiple contributing authors.
Verified PDF · Secure download - Introduction to Descriptive Statistics
Lecture notes covering data types, sampling methods, experimental design, measures of central tendency, correlation, and confidence intervals. Focused and practical approach to descriptive methods.
Verified PDF · Secure download - Introduction to Biostatistics
Applied biostatistics covering study design, survival analysis, logistic regression, clinical trials, and epidemiological methods for healthcare and life sciences.
Verified PDF · Secure download - An Introduction to Bayesian Thinking
Coursera companion textbook covering Bayesian inference from foundations to advanced modeling. Includes prior elicitation, hypothesis testing, regression, and model selection using R and BAS package.
Verified PDF · Secure download
