Experimental Design and Data Analysis for Biologists
| AUTHOR | Quinn, Gerry P.; Keough, Michael J. |
| PUBLISHER | Cambridge University Press (11/16/2023) |
| PRODUCT TYPE | Paperback (Paperback) |
Description
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.
Show More
Product Format
Product Details
ISBN-13:
9781107687677
ISBN-10:
1107687675
Binding:
Paperback or Softback (Trade Paperback (Us))
Content Language:
English
Edition Number:
0002
More Product Details
Page Count:
405
Carton Quantity:
10
Product Dimensions:
7.95 x 0.87 x 9.92 inches
Weight:
2.15 pound(s)
Feature Codes:
Bibliography,
Glossary
Country of Origin:
GB
Subject Information
BISAC Categories
Science | Life Sciences - Biology
Dewey Decimal:
570.151
Library of Congress Control Number:
2023005179
Descriptions, Reviews, Etc.
publisher marketing
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.
Show More
List Price $59.99
Your Price
$59.39
