Monty the Null Hippopotamus
CRC Press (Verlag)
978-1-041-25711-0 (ISBN)
- Noch nicht erschienen (ca. April 2026)
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Monty the Null Hippopotamus: Exploring Statistical Foundations Through Simulation offers a revolutionary approach to introductory statistics designed for students who grew up in the computing age. Breaking away from the traditional formula-memorization approach that makes "Stat 101" a dreaded requirement, this book emphasizes computational thinking and conceptual understanding through hands-on coding examples. The aim is to make statistics accessible and engaging by leveraging modern computing power rather than relying on memorizing inscrutable formulas, punching in tedious calculations into calculators, and flipping through pages of statistical tables.
The book covers foundational statistical concepts through advanced topics including nonparametric methods and regression analysis, all presented through a computational lens that prioritizes process over precision. Every concept is illustrated with fully reproducible R code (with Python alternatives available), ensuring readers develop genuine intuition for how statistical methods actually work in practice.
Features:
• Emphasizes simulation and Monte Carlo methods over formula memorization
• Every statistical concept illustrated with fully reproducible R and Python examples
• Comprehensive coverage, from basic inference to nonparametrics and regression
• Graduated homework exercises combining theory with real-world data analysis
• More than thirty data sets supporting examples and homework exercises
• Favors understanding over pedantry, with extensive web links and contextual references
The book is designed for undergraduate students comfortable with probability, calculus, and basic programming concepts. It serves as an ideal text for introductory statistics courses, and is equally valuable for graduate students from non-statistical backgrounds seeking a modern foundation in statistical thinking. The narrative emphasizes active reading and coding practice rather than passive consumption, making it perfect for students who are ready to engage deeply with statistical concepts through hands-on exploration.
Robert B. Gramacy is a Professor of Statistics at Virginia Tech (VT), and Fellow of the American Statistical Association. At VT he also serves affiliate faculty in the Computational Modeling and Data Analytics program, and core faculty in the Center for Ecosystem Forecasting. His research interests include Bayesian modeling methodology, statistical computing, Monte Carlo inference, nonparametric regression, surrogate modeling, uncertainty quantification, sequential design, and optimization under uncertainty.
1 Toss up: coin flips. 2 Location: mean modeling. 3 A little math: inference. 4 A little math: asymptotics. 5 Two samples. 6 Analysis of variance. 7 Correlation & linear regression. 8 Bootstrap & permutation. 9 Non-P location. 10 Pearson χ² tests. 11 Non-P scale. 12 Non-P correlation & regression. 13 Fancy regression.
| Erscheint lt. Verlag | 20.4.2026 |
|---|---|
| Zusatzinfo | 18 Tables, black and white; 82 Line drawings, black and white; 82 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 178 x 254 mm |
| Themenwelt | Mathematik / Informatik ► Mathematik |
| ISBN-10 | 1-041-25711-2 / 1041257112 |
| ISBN-13 | 978-1-041-25711-0 / 9781041257110 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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