

Probability and Conditional Expectation – Fundamentals for the Empirical Sciences
1 106,-

Understanding Uncertainty, Revised Edition
1 214,-

Bayes Linear Statistics – Theory and Methods
1 646,-

Inference and Prediction in Large Dimensions
1 106,-

Markov Decision Processes – Discrete Stochastic Dynamic Programming
1 592,-

Bayesian Statistical Modelling 2e
1 106,-

Structural Equation Modeling – A Bayesian Approach
1 277,-

Linear Models – The Theory and Application of Analysis of Variance
1 439,-

Stage–Wise Adaptive Designs
1 592,-

Response Surfaces, Mixtures and Ridge Analyses 2e
1 862,-

Probability and Conditional Expectation – Fundamentals for the Empirical Sciences
1 106,-

Understanding Uncertainty, Revised Edition
1 214,-

Bayes Linear Statistics – Theory and Methods
1 646,-

Inference and Prediction in Large Dimensions
1 106,-

Markov Decision Processes – Discrete Stochastic Dynamic Programming
1 592,-

Bayesian Statistical Modelling 2e
1 106,-

Structural Equation Modeling – A Bayesian Approach
1 277,-

Linear Models – The Theory and Application of Analysis of Variance
1 439,-

Stage–Wise Adaptive Designs
1 592,-

Response Surfaces, Mixtures and Ridge Analyses 2e
1 862,-















