Planning, Construction, and Statistical Analysis of Comparative Experiments

A valuable guide to conducting experiments and analyzingdata across a wide range of applications
Experimental design is an important component of the scientific method. Thisbook provides guidance on planning efficient investigations. It compilesdesigns for a wide range of experimental situations not previously found inaccessible form. Focusing on applications in the physical, engineering,biological, and social sciences, Planning, Construction, and StatisticalAnalysis of Comparative Experiments is a valuable guide to designingexperiments and correctly analyzing and interpreting the results. The authorsdraw on their years of experience in the classroom and as statisticalconsultants to research programs on campus, in government, and in industry. Theobject is always to strike the right balance between mathematical necessitiesand practical constraints.
Serving both as a textbook for students of intermediatestatistics and a hands–on reference for active researchers, the text includes: A wide range of applications, including agricultural sciences, animal and biomedical sciences, and industrial engineering studiesGeneral formulas for estimation and hypothesis testing, presented in a unified and simplified mannerGuidelines for evaluating the power and efficiency of designs that are not perfectly balancedNew developments in the design of fractional factorials with non–prime numbers of levels in mixed–level fractional factorialsDetailed coverage on the construction of plans and the relationship among categories of designsThorough coverage of balanced, lattice, cyclic, and alpha designsStrategies for sequences of fractional factorialsData sets and SAS® code on a companion web site
An ideal handbook for the investigator planning a researchprogram, the text comes complete with detailed plans of experiments andalternative approaches for added flexibility.

S pis treści:
Preface.
Introduction.
The Completely Randomized Design.
Linear Models for Designed Experiments.
Testing Hypotheses and Determining Sample Size.
Methods of Reducing Unexplained Variation.
Latin Squares.
Split–Plot and Related Designs.
Incomplete Block Designs.
Repeated Teatments Designs.
Factorial Experiments, the 2n System.
Factorial Experiments, the 3n System.
Analysis of Experiments Without Designed Error Terms.
Confounding Effects with Blocks.
Fractional Factorial Experiments.
Response Surface Designs.
Plackett–Burmann Hadamard Plans.
The General Pn and Nonstandard Factorials.
Factorial Experiments with Quantitative Factors.
Plans for Which Run Order is Important.
Supersaturated Plans.
Sequences of Fractions of Factorials.
Multi–Stage xperiments.
Orthogonal Arrays and Related Structures.
Factorial Plans Derived via Orthogonal Arrays.
Experiments on the Computer.

Nota biograficzna:
FRANCIS G. GIESBRECHT, PhD, is Professor Emeritus in the Department of Statistics at North Carolina State University in Raleigh, North Carolina. He earned his PhD in Statistics from the Iowa State University.
MARCIA L. GUMPERTZ, PhD, is a professor in the Department of Statistics at North Carolina State University where she also received her PhD in Statistics.

Okładka tylna:
A valuable guide to conducting experiments and analyzingdata across a wide range of applications
Experimental design is an important component of the scientific method. Thisbook provides guidance on planning efficient investigations. It compilesdesigns for a wide range of experimental situations not previously found inaccessible form. Focusing on applications in the physical, engineering,biological, and social sciences, Planning, Construction, and StatisticalAnalysis of Comparative E xperiments is a valuable guide to designingexperiments and correctly analyzing and interpreting the results. The authorsdraw on their years of experience in the classroom and as statisticalconsultants to research programs on campus, in government, and in industry. Theobject is always to strike the right balance between mathematical necessitiesand practical constraints.
Serving both as a textbook for students of intermediatestatistics and a hands–on reference for active researchers, the text includes: A wide range of applications, including agricultural sciences, animal and biomedical sciences, and industrial engineering studiesGeneral formulas for estimation and hypothesis testing, presented in a unified and simplified mannerGuidelines for evaluating the power and efficiency of designs that are not perfectly balancedNew developments in the design of fractional factorials with non–prime numbers of levels in mixed–level fractional factorialsDetailed coverage on the construction of plans and the relationship among categories of designsThorough coverage of balanced, lattice, cyclic, and alpha designsStrategies for sequences of fractional factorialsData sets and SAS® code on a companion web site
An ideal handbook for the investigator planning a researchprogram, the text comes complete with detailed plans of experiments andalternative approaches for added flexibility.