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Published by Princeton University Press, 2025
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Published by Princeton University Press, US, 2025
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Paperback. Condition: New. 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.
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ISBN 10: 0691258775 ISBN 13: 9780691258775
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ISBN 10: 0691258775 ISBN 13: 9780691258775
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Paperback. Condition: New. 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.
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ISBN 10: 0691258775 ISBN 13: 9780691258775
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ISBN 10: 0691258775 ISBN 13: 9780691258775
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Paperback. Condition: new. Paperback. 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 Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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ISBN 10: 0691258775 ISBN 13: 9780691258775
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Published by Springer Fachmedien Wiesbaden, Weisbaden, 2017
ISBN 10: 3662546833 ISBN 13: 9783662546833
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Paperback. Condition: new. Paperback. Beispielreich baut dieses Buch Schritt fuer Schritt die statistischen Grundlagen moderner Datenanalysen auf. Im Gegensatz zu anderen einfuehrenden Werken legt dieses Buch grossen Wert auf einen umfassend gespannten Bogen, einen roten Faden, der alle Methoden zusammenfuehrt. Dabei werden klassische statistische Methoden (etwa t-Test oder multiple Regression) als Spezialfall des Generalisierten Linearen Modells entwickelt. Entsprechend legt das Buch zunaechst eine Grundlage in beschreibender Statistik, Verteilungen und maximum likelihood, aus der dann alle anderen Verfahren abgeleitet werden (ANOVA, multiple Regression). Jeder Schritt ist auf zwei Kapitel verteilt: Im ungradzahligen Kapitel wird anhand von vielen Beispielen und Abbildungen die Idee der statistischen Herangehensweise erlaeutert. Im sich daran anschliessenden gradzahligen Kapitel wird die Umsetzung in der freien Statistiksoftware R gezeigt. Ein Kapitel zur Wissenschafts- und Forschungstheorie und eines zum Design von Experimenten und Stichprobeverfahren komplettiert dieses einleitende Werk. Das Buch legt grossen Wert auf Verstaendlichkeit und Umsetzung. Mathematische Herleitungen treten demgegenueber stark in den Hintergrund. Jedes Kapitel enthaelt explizit ausgewiesene Lerninhalte, die durch UEbungen zu jedem R-Kapitel geprueft werden koennen. Ein ausfuehrliches Schlagwortverzeichnis inklusive der R-Funktionen macht das Buch auch als Nachschlagewerk nutzbar. Die zweite Auflage wurde ergaenzt um Schaetzung mittels der Momentenmethode, Residuendiagnostik fuer nicht-normalverteilte Daten und die erschoepfende Modellsuche. Ein Kapitel zur Wissenschafts- und Forschungstheorie und eines zum Design von Experimenten und Stichprobeverfahren komplettiert dieses einleitende Werk. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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