Santiago Barreda is a phonetician in the Linguistics Department at the University of California, Davis, USA, with a particular interest in speech perception.

Noah Silbert is a former Academic and is currently a practicing Stoic. His training and background are in phonetics, perceptual modeling, and statistics.

Preface

Acknowledgments

1. Introduction: Experiments and Variables

2. Probabilities, Likelihood, and Inference

3. Fitting Bayesian Regression Models with brms

4. Inspecting a 'Single Group' of Observations using a Bayesian Multilevel Model

5. Comparing Two Groups of Observations: Factors and Contrasts

6. Variation in Parameters ('Random Effects') and Model Comparison

7. Comparing Many Groups, Interactions, and Posterior Predictive Checks

8. Varying Variances, More about Priors, and Prior Predictive Checks

9. Quantitative Predictors and their Interactions with Factors

10. Logistic Regression and Signal Detection Theory Models

11. Multiple Quantitative Predictors, Dealing with Large Models, and Bayesian ANOVA

12. Multinomial and Ordinal Regression

13. Writing up Experiments: An investigation of the Perception of Apparent Speaker Characteristics from Speech Acoustics