Statistics by Simulation

Statistics by Simulation: A Synthetic Data Approach

Architect your analytical logic and master the high-performance protocols of modern statistical engineering. Statistics by Simulation provides a definitive, intelligence-first roadmap to the most significant shift in data science since the digital revolution. Learn how to move beyond black-box formulas to high-velocity, simulation-driven discovery—bridging the gap between a raw dataset and a sophisticated, synthetic data ecosystem—ensuring your technical projects are resilient, scalable, and ready for the 2026 global technology landscape.

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What You Will Learn:

Foundations of Simulation Architecture: Master the core principles of using "virtual experiments" to understand complex statistical distributions and the mechanics of frequentist and Bayesian inference.

Modern Synthetic Workflows: Step-by-step guidance on generating synthetic datasets to test the structural integrity of your models before applying them to real-world data.

Scalable Modeling Patterns: Discover how to utilize R-based simulations to maintain the technical agility of your linear models, GLMs, and mixed-effect structures.

Strategic Security & Empirical Integrity: Learn advanced techniques for maintaining information security within your research, using synthetic data to protect sensitive primary sources while ensuring the technical agility of your reproducible results.

Who This Book is For: This professional-grade guide is essential for Ecologists, Data Scientists, and Quantitative Researchers. It is an invaluable resource for any technical lead—including those building highly advanced, data-driven graduation projects like Smart Guard—aiming to master the structural integrity and technical agility required for modern, evidence-based software and system delivery.

Product Details:

Format: Digital PDF Download

Authors: Carsten F. Dormann; Aaron M. Ellison

Publisher: Princeton University Press

ISBN-13: 9780691258775

ISBN-10: 0691258775