Introduction to the Design & Analysis of Experiments

by Canavos, George C; Koutrouvelis, John A.

• ISBN13: 9780136158639
• ISBN10: 0136158633
• Edition: 1st
• Format: Hardcover
• Copyright: 2008-02-24
• Publisher: Pearson

Summary

<>Key Message:Introduction to the Design & Analysis of Experimentsintroduces readers to the design and analysis of experiments. It is ideal for a one-semester, upper-level undergraduate course for majors in statistics and other mathematical sciences, natural sciences, and engineering. It may also serve appropriate graduate courses in disciplines such as business, health sciences, and social sciences. This book assumes that the reader has completed a two-semester sequence in the application of probability and statistical inference. Key Topics: An Introduction to the Design of Experiments; Investigating a Single Factor: Completely Randomized Experiments; Investigating a Single Factor: Randomized Complete and Incomplete Block and Latin Square Designs; Factorial Experiments: Completely Randomized Designs; Factorial Experiments: Randomized Block and Latin Square Designs; Nested Factorial Experiments and Repeated Measures Designs;2fand3fFactorial Experiments; Confounding in2fand3fFactorial Experiments; Fractional Factorial Experiments0; Regression Analysis: The General Linear Model; Response Surface Designs for First and Second-Order Models Market: For all readers interested in experimental design.

Table of Contents

An Introduction to the Design of Experiments

Introduction

The Use of Designed Experiments in Process Studies

Fundamental Aspects of Designed Experiments

Documentation Form for a Designed Experiment

Summary

References

Exercises

Investigating a Single Factor: Completely Randomized Experiments

Introduction and Graphical Analysis of Sample Data

The Analysis of Variance Approach: Partitioning the Total Variation in the Data

Analysis of Variance for a Fixed Effects Model

Analysis of Variance for a Random Effects Model

Methods for Multiple Comparisons

Tukey's Method for Multiple Comparisons

Scheffeacute;'s Method for Multiple Comparisons

Potential Consequences of Violating Analysis of Variance Assumptions

The Use of P-values in Testing Statistical Hypotheses

Summary

References

Exercises

Introduction to and Computer Instructions for Using Minitab, Release 15

Investigating a Single Factor: Randomized Complete and Incomplete Block and Latin Square Designs

Introduction

Analysis of Variance for Blocked Data: Partitioning the Total Variation in the Data

Assumptions and Validity of Analysis of Variance for Randomized Complete Block Designs

Tukey and Scheffeacute;'s Procedures for a Randomized Complete Block Design

Balanced Incomplete Block Designs

Latin Square Designs

Analysis of Variance for Latin Square Designs: Partitioning the Total Variation in the Data

Assumptions and Validity of the Analysis of Variance for Latin Square Designs

Summary

References

Exercises

Minitab Instructions

Factorial Experiments: Completely Randomized Designs

Introduction

Inference Objectives in Factorial Experiments: Main Effects and Interaction Effects

Complete Randomization in Factorial Experiments

Graphical Analysis

Analysis of Variance Procedure: Partitioning the Total Sum of Squares

No Replication in Factorial Experiments

Fixed, Random, and Mixed Models: Expected Mean Squares

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