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Published by Princeton University Press, 2025
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Softcover. Condition: Fair. Spuren von Feuchtigkeit / Nässe; Leichte Rillen / Abschürfungen / Risse / Knicke. Dieses Buch vermittelt schrittweise die statistischen Grundlagen moderner Datenanalysen und legt dabei großen Wert auf einen klaren roten Faden, der alle Methoden miteinander verbindet. Klassische statistische Verfahren wie der t-Test oder die multiple Regression werden als spezielle Fälle des Generalisierten Linearen Modells betrachtet. Zunächst wird eine Basis in beschreibender Statistik, Verteilungen und Maximum Likelihood geschaffen, von der aus alle weiteren Verfahren wie ANOVA und multiple Regression abgeleitet werden. Jeder Schritt ist in zwei Kapitel unterteilt: Im ungeraden Kapitel werden die Ideen der statistischen Herangehensweise anhand zahlreicher Beispiele und Abbildungen erläutert, während das folgende gerade Kapitel die praktische Umsetzung in der Statistiksoftware R zeigt. Ergänzt wird das Werk durch ein Kapitel zur Wissenschafts- und Forschungstheorie sowie eines zum Design von Experimenten und Stichprobenverfahren. Das Buch legt besonderen Wert auf Verständlichkeit und praktische Anwendung, während mathematische Herleitungen in den Hintergrund treten. Jedes Kapitel enthält klar ausgewiesene Lerninhalte, die durch Übungen zu den R-Kapiteln vertieft werden können. Ein umfassendes Schlagwortverzeichnis mit R-Funktionen macht das Buch auch als Nachschlagewerk nützlich. Die zweite Auflage umfasst zudem neue Themen wie die Momentenmethode, Residuendiagnostik für nicht-normalverteilte Daten und umfassende Model.
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Published by Princeton University Press, 2025
ISBN 10: 0691258775 ISBN 13: 9780691258775
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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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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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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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