Contents
Preface
0. Introduction
I. Describing single variables
1. Arithmetic and variables: The lifeblood of modeling
2. Functions and their graphs
3. Describing data sets
4. Random variables and distributions
5. Estimation from a random sample
II. Relationship between two variables
6. Independence of random variables
7. Bayes' amazing formula
8. Linear regression and correlation
9. Nonlinear data fitting
III. Chains of random variables
10. Markov models with discrete states
11. Probability distributions of Markov chains
12. Stationary distributions of Markov chains
13. Dynamics of Markov models
IV. Variables that change with time
14. Linear difference equations
15. Linear ordinary differential equations
16. Graphical analysis of ordinary differential equations
17. Chaos and bifurcations in difference equations
Bibliography
Index