While the book avoids heavy measure theory, it requires high mathematical maturity and strong calculus skills.
| Chapter | Title | | :--- | :--- | | 1 | Preliminaries | | 2 | The Poisson Process | | 3 | Renewal Theory | | 4 | Markov Chains | | 5 | Continuous-Time Markov Chains | | 6 | Martingales | | 7 | Random Walks | | 8 | Brownian Motion and Other Markov Processes | | 9 | Stochastic Order Relations | | 10 | Poisson Approximations |
Don't just copy the final number. Study the methodology of the solution to understand why a particular stochastic technique was applied.
🔍 The blog's Chapter 4 solution (covering Markov Chains) and Chapter 7 solution (covering Random Walks) are particularly helpful, as these topics are widely considered the most challenging in the book.