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Associate Professor EdwardDurner

Applied Plant Science Experimental Design and Statistical Analysis Using SAS (R) OnDemand for Academics

Applied Plant Science Experimental Design and Statistical Analysis Using SAS (R) OnDemand for Academics

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  • More about Applied Plant Science Experimental Design and Statistical Analysis Using SAS (R) OnDemand for Academics


SAS® is the most widely used statistical software in the world, and SAS® OnDemand for Academics is now freely available for academic institutions. This guide provides a user-friendly introduction to statistics using SAS® OnDemand for Academics, ideal for facilitating the design and analysis of plant science experiments. It covers experimental designs, data analysis protocols, and key topics such as merging data frames, multivariate analysis, and linear regression. Authored by an experienced teacher of applied plant science statistics, the book assumes no prior background in statistics and guides users through the appropriate methodologies in research.

Format: Paperback / softback
Length: 416 pages
Publication date: 10 June 2021
Publisher: CABI Publishing


The correct design, analysis, and interpretation of plant science experiments are essential for advancing agricultural production worldwide. With a vast array of options available for implementing, analyzing, and interpreting research, it can be overwhelming to navigate through them. SAS® is the most widely used statistical software globally, and SAS® OnDemand for Academics is now freely accessible to academic institutions. This user-friendly guide to statistics using SAS® OnDemand for Academics is designed to facilitate the design and analysis of plant science experiments. It presents the most commonly used statistical methods in a straightforward and non-intimidating manner, ensuring that readers can effectively utilize SAS® within the context of plant science research.

This comprehensive book covers experimental designs and data analysis protocols, presenting them as a step-by-step guide with numerous examples. It also includes freely downloadable data sets, allowing readers to apply the techniques learned directly to their own research. Key topics such as merging data frames, multivariate analysis, and linear regression are examined in depth, providing readers with a solid foundation in statistical methodologies. Authored by an experienced teacher of applied plant science statistics, this book assumes no prior background in statistics and guides users through the appropriate methodologies in research. Whether you are an advanced undergraduate or graduate student, researcher, extension consultant, faculty member, or technician, this book is an invaluable tool for advancing your understanding of plant science statistics and improving your research outcomes.

Weight: 1144g
Dimension: 189 x 245 x 34 (mm)
ISBN-13: 9781789245981

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