About this product

Product Identifiers

PublisherPrinceton University Press

ISBN-100691273898

ISBN-139780691273891

eBay Product ID (ePID)8070930486

Product Key Features

Number of Pages456 Pages

LanguageEnglish

Publication NameStatistics by Simulation : a Synthetic Data Approach

SubjectComputer Simulation, Probability & Statistics / General, General, Research & Methodology

Publication Year2025

TypeTextbook

Subject AreaMathematics, Computers, Science

AuthorCarsten F. Dormann, Aaron M. Ellison

FormatHardcover

Dimensions

Item Height1.2 in

Item Weight36 Oz

Item Length10.2 in

Item Width7.4 in

Additional Product Features

Intended AudienceCollege Audience

LCCN2024-054271

Dewey Edition23

IllustratedYes

Dewey Decimal519.5

SynopsisAn 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, 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

LC Classification NumberQA276.4.D67 2025