Applied Plant Science Experimental Design and Statistical Analysis Using SAS® OnDemand for Academics
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A01=Associate Professor Edward Durner
A01=Edward F Durner
Age Group_Uncategorized
Age Group_Uncategorized
analysis of a series of experiments
analysis of covaraiance
analysis of covariance
analysis of variance
applied plant science
Author_Associate Professor Edward Durner
Author_Edward F Durner
automatic-update
blocking
Category1=Non-Fiction
Category=GPS
Category=PST
completely random design
COP=United Kingdom
data transformation
Delivery_Delivery within 10-20 working days
eq_bestseller
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_science
expected mean squares
experimental design
Language_English
latin square design
linear regression
mean separation
meant separation techniques
non-parametric procedures
PA=Available
plant science research and experimentation
presentation of research results
Price_€20 to €50
PS=Active
randomization
randomized complete block design
regression diagnostics
sampling
SAS University Edition
softlaunch
split-plot design
Statistical analysis
Product details
- ISBN 9781789245981
- Weight: 1142g
- Dimensions: 189 x 246mm
- Publication Date: 10 Jun 2021
- Publisher: CABI Publishing
- Publication City/Country: GB
- Product Form: Paperback
- Language: English
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The correct design, analysis and interpretation of plant science experiments is imperative for continued improvements in agricultural production worldwide. The enormous number of design and analysis options available for correctly implementing, analysing and interpreting research can be overwhelming. SAS® is the most widely used statistical software in the world and SAS® OnDemand for Academics is now freely available for academic institutions. This is a user-friendly guide to statistics using SAS® OnDemand for Academics, ideal for facilitating the design and analysis of plant science experiments. It presents the most frequently used statistical methods in an easy-to-follow and non-intimidating fashion, and teaches the appropriate use of SAS® within the context of plant science research. This book: - Covers experimental designs and data analysis protocols - Is presented as a how-to guide with many examples - Includes freely downloadable data sets - Examines key topics such as merging data frames, multivariate analysis and linear regression 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. It is an invaluable tool for advanced undergraduate and graduate students, in addition to researchers, extension consultants, faculty and technicians.
I received my BS in Horticulture from the University of Maryland, College Park, MD, my MS in Horticulture from Virginia Tech, Blacksburg, VA, and my Ph.D. in Horticultural Science from North Carolina State University, Raleigh, NC. I joined the Horticulture Department at Rutgers in 1986 and conducted tree fruit physiology research, including peach flower bud cold hardiness, rootstock - scion interactions in peach and apple and consumer acceptance of disease resistant apple cultivars. From the late 1990's through 2005 my research focused on photoperiod and temperature conditioning of strawberry plug plants for off-season production. From 2006 - 2016 my research program was placed on hiatus to serve as Director of the Student Sustainable Farm at Rutgers, a student-run 5-acre CSA (Community Supported Agriculture) farm with 50 to 175 shareholders that provided experiential learning of organic vegetable, herb and flower production for students at Rutgers - The State University of New Jersey. In 2016 I returned to my roles in teaching and research, investigating alternative strawberry production systems and plant conditioning and goldenberry (Physalis peruviana) as a new fruit crop for North America. I teach or have taught 'Applied Plant Science Statistics', 'Applied Physiology of Hort Crops', 'Agroecology Practicum', 'Fruit Production', 'Seminar in Horticulture' and 'Perspectives on Agriculture & the Environment'.
