Statistics by Simulation : A Synthetic Data Approach

Carsten F Dormann

ISBN 10: 0691273898 / ISBN 13: 9780691273891

Published by Princeton University Press Jun 2025, 2025

About this Item

Neuware - An accessible guide to understanding statistics using simulations, with examples from a range of scientific disciplinesReal-world challenges such as small sample sizes, skewed distributions of data, biased sampling designs, and more predictors than data points are pushing the limits of classical statistical analysis. This textbook provides a new tool for the statistical toolkit: data simulations. It shows that using simulation and data-generating models is an excellent way to validate statistical reasoning and to augment study design and statistical analysis with planning and visualization. Although data simulations are not new to professional statisticians, Statistics by Simulation makes the approach accessible to a broader audience, with examples from many fields. It introduces the reasoning behind data simulation and then shows how to apply it in planning experiments or observational studies, developing analytical workflows, deploying model diagnostics, and developing new indices and statistical methods. Covers all steps of statistical practice, from planning projects to post-hoc analysis and model checking Provides examples from disciplines including sociology, psychology, ecology, economics, physics, and medicine Includes R code for all examples, with data and code freely available online Offers bullet-point outlines and summaries of each chapter Minimizes the use of jargon and requires only basic statistical background and skills.

Seller Inventory # 9780691273891

Bibliographic Details

• Title: Statistics by Simulation : A Synthetic Data Approach
• Publisher: Princeton University Press Jun 2025
• Publication Date: 2025
• Language: English
• ISBN 10: 0691273898
• ISBN 13: 9780691273891
• Binding: Buch
• Condition: Neu
• Dimensions: 256W x 182H x 32D millimeters 256 millimeters width by 182 millimeters height by 32 millimeters depth
• Weight: 1026 grams

About this title

Synopsis

An accessible guide to understanding statistics using simulations, with examples from a range of scientific disciplines

Real-world challenges such as small sample sizes, skewed distributions of data, biased sampling designs, and more predictors than data points are pushing the limits of classical statistical analysis. This textbook provides a new tool for the statistical toolkit: data simulations. It shows that using simulation and data-generating models is an excellent way to validate statistical reasoning and to augment study design and statistical analysis with planning and visualization. Although data simulations are not new to professional statisticians, Statistics by Simulation makes the approach accessible to a broader audience, with examples from many fields. It introduces the reasoning behind data simulation and then shows how to apply it in planning experiments or observational studies, developing analytical workflows, deploying model diagnostics, and developing new indices and statistical methods.

• Covers all steps of statistical practice, from planning projects to post-hoc analysis and model checking
• Provides examples from disciplines including sociology, psychology, ecology, economics, physics, and medicine
• Includes R code for all examples, with data and code freely available online
• Offers bullet-point outlines and summaries of each chapter
• Minimizes the use of jargon and requires only basic statistical background and skills

About the Author

Carsten F. Dormann is professor of biometry and environmental system analysis at the University of Freiburg, Germany. He is the author of the introductory textbook Environmental Data Analysis and coauthor of an open marine ecology textbook, Marine Ecology Notes. Aaron M. Ellison served for twenty years as the senior research fellow in ecology at Harvard University. He is the author of A Field Guide to the Ants of New England and Vanishing Point and coauthor of A Primer of Ecological Statistics, Scaling in Ecology with a Model System, and other books.