Design and Analysis of Experiments with R

Regular price €127.99
A01=John Lawson
advanced experimental design techniques
agricultural experiments
analyze experimental data using R
ANOVA Table
applied statistics
Author_John Lawson
Bib Design
Category=UFM
Central Composite Design
Coded Factor Levels
creating the experimental design
Defining Relation
Definitive Screening Designs
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experimental design choice
experimental designs
experimental methodology
Experimental Units
Fractional Factorial
Fractional Factorial Split Plot Design
General Quadratic Model
Half Normal Plot
industrial process optimisation
Interpret the results of computer data analysis
Orthogonal Array
Orthogonal Main Effect Plans
PB Design
RCB Design
REML Estimate
REML Method
research data analysis
Resolution III
Resolution Iv Design
Response Surface Design
Small Composite Design
Split Plot Design
Split Plot Experiments
statistical modelling
Sub-plot Factor
Subplot Factors

Product details

  • ISBN 9781439868133
  • Weight: 1310g
  • Dimensions: 156 x 234mm
  • Publication Date: 17 Dec 2014
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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Design and Analysis of Experiments with R presents a unified treatment of experimental designs and design concepts commonly used in practice. It connects the objectives of research to the type of experimental design required, describes the process of creating the design and collecting the data, shows how to perform the proper analysis of the data, and illustrates the interpretation of results.

Drawing on his many years of working in the pharmaceutical, agricultural, industrial chemicals, and machinery industries, the author teaches students how to:

  • Make an appropriate design choice based on the objectives of a research project
  • Create a design and perform an experiment
  • Interpret the results of computer data analysis

The book emphasizes the connection among the experimental units, the way treatments are randomized to experimental units, and the proper error term for data analysis. R code is used to create and analyze all the example experiments. The code examples from the text are available for download on the author’s website, enabling students to duplicate all the designs and data analysis.

Intended for a one-semester or two-quarter course on experimental design, this text covers classical ideas in experimental design as well as the latest research topics. It gives students practical guidance on using R to analyze experimental data.

John Lawson is a professor in the Department of Statistics at Brigham Young University.