Design and Analysis of Experiments with R - John Lawson

Design and Analysis of Experiments with R

(Autor)

Buch | Hardcover
628 Seiten
2014
Chapman & Hall/CRC (Verlag)
978-1-4398-6813-3 (ISBN)
137,15 inkl. MwSt
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.

Introduction. Completely Randomized Designs with One Factor. Factorial Designs. Randomized Block Designs. Designs to Study Variances. Fractional Factorial Designs. Incomplete and Confounded Block Designs. Split-Plot Designs. Crossover and Repeated Measures Designs. Response Surface Designs. Mixture Experiments. Robust Parameter Design Experiments. Experimental Strategies for Increasing Knowledge. Bibliography. Index.

Reihe/Serie Chapman & Hall/CRC Texts in Statistical Science
Zusatzinfo 168 Tables, black and white; 162 Illustrations, black and white
Sprache englisch
Maße 156 x 234 mm
Gewicht 1310 g
Themenwelt Mathematik / Informatik Mathematik Computerprogramme / Computeralgebra
Naturwissenschaften Biologie
Technik Umwelttechnik / Biotechnologie
ISBN-10 1-4398-6813-1 / 1439868131
ISBN-13 978-1-4398-6813-3 / 9781439868133
Zustand Neuware
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