Bayesian Data Analysis for the Behavioral and Neural Sciences: Non-Calculus Fundamentals
Cambridge University Press, 6/24/2021
EAN 9781108835565, ISBN10: 1108835562
Hardcover, 2 pages, 25.7 x 20.6 x 3 cm
Language: English
Originally published in English
This textbook bypasses the need for advanced mathematics by providing in-text computer code, allowing students to explore Bayesian data analysis without the calculus background normally considered a prerequisite for this material. Now, students can use the best methods without needing advanced mathematical techniques. This approach goes beyond “frequentist†concepts of p-values and null hypothesis testing, using the full power of modern probability theory to solve real-world problems. The book offers a fully self-contained course, which demonstrates analysis techniques throughout with worked examples crafted specifically for students in the behavioral and neural sciences. The book presents two general algorithms that help students solve the measurement and model selection (also called “hypothesis testingâ€Â) problems most frequently encountered in real-world applications.
1. Logic and data analysis
2. Mechanics of probability calculations
3. Probability and information
from priors to posteriors
4. Prediction and decision
5. Models and measurements
6. Model selection
Appendix A. Coding basics
Appendix B. Mathematics review
logarithmic and exponential function
Appendix C. The Bayesian toolbox
marginalization and coordinate transformations.