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| Titre : | Experimental design and data analysis for biologists | | Type de document : | texte imprimé | | Auteurs : | Gerry P. Quinn, Auteur ; Michael J. Keough, Auteur | | Mention d'édition : | Second Edition | | Editeur : | Cambridge University Press | | Année de publication : | 2023 | | Importance : | 1 vol. (XIX-387 p.) | | Présentation : | ill.en coul. | | Format : | 26 cm | | ISBN/ISSN/EAN : | 978-1-107-03671-0 | | Langues : | Anglais | | Catégories : | Biologie ( B-Cellulaire - B-Animale - B-Végétale - B-moléculaire - Cytologie )
| | Mots-clés : | biology experiment model statistics design | | Index. décimale : | 570.285 Informatique appliquée à la biologie et aux sciences de la vie - bio-informatique - | | Résumé : |
Applying statistical concepts to biological scenarios, this established textbook continues to be the go-to tool for advanced undergraduates and postgraduates studying biostatistics or experimental design in biology-related areas. Chapters cover linear models, common regression and ANOVA methods, mixed effects models, model selection, and multivariate methods used by biologists, requiring only introductory statistics and basic mathematics. Demystifying statistical concepts with clear, jargon-free explanations, this new edition takes a holistic approach to help students understand the relationship between statistics and experimental design. Each chapter contains further-reading recommendations, and worked examples from today's biological literature. All examples reflect modern settings, methodology and equipment, representing a wide range of biological research areas. These are supported by hands-on online resources including real-world data sets, full R code to help repeat analyses for all worked examples, and additional review questions and exercises for each chapter. | | Note de contenu : |
Sommaire:
-1- Introduction
-2- Things to know before proceeding
-3- Sampling and exprimental desing
-4- Introduction to linear models
-5- Exploratory data analysis
-6- Simple linear models with one predictor
-7- Linear models for crossed (Factorial) designs
-8- Multiple regression models |
Experimental design and data analysis for biologists [texte imprimé] / Gerry P. Quinn, Auteur ; Michael J. Keough, Auteur . - Second Edition . - [S.l.] : Cambridge University Press, 2023 . - 1 vol. (XIX-387 p.) : ill.en coul. ; 26 cm. ISBN : 978-1-107-03671-0 Langues : Anglais | Catégories : | Biologie ( B-Cellulaire - B-Animale - B-Végétale - B-moléculaire - Cytologie )
| | Mots-clés : | biology experiment model statistics design | | Index. décimale : | 570.285 Informatique appliquée à la biologie et aux sciences de la vie - bio-informatique - | | Résumé : |
Applying statistical concepts to biological scenarios, this established textbook continues to be the go-to tool for advanced undergraduates and postgraduates studying biostatistics or experimental design in biology-related areas. Chapters cover linear models, common regression and ANOVA methods, mixed effects models, model selection, and multivariate methods used by biologists, requiring only introductory statistics and basic mathematics. Demystifying statistical concepts with clear, jargon-free explanations, this new edition takes a holistic approach to help students understand the relationship between statistics and experimental design. Each chapter contains further-reading recommendations, and worked examples from today's biological literature. All examples reflect modern settings, methodology and equipment, representing a wide range of biological research areas. These are supported by hands-on online resources including real-world data sets, full R code to help repeat analyses for all worked examples, and additional review questions and exercises for each chapter. | | Note de contenu : |
Sommaire:
-1- Introduction
-2- Things to know before proceeding
-3- Sampling and exprimental desing
-4- Introduction to linear models
-5- Exploratory data analysis
-6- Simple linear models with one predictor
-7- Linear models for crossed (Factorial) designs
-8- Multiple regression models |
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Affiner la rechercheExperimental design and data analysis for biologists / Gerry P. Quinn / Cambridge University Press (2023)
