Effective Experimentation For Scientists and Technologists

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ISBN: 9780470684603 | 0470684607
Cover: Hardcover
Copyright: 8/9/2010

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This book has been developed from courses run by Statistics for Industry Limited for the past 30 years and demonstrates the ways in which statistical methods can be applied successfully, each method is introduced and used in a real situation from industry or research, each chapter includes examples obtained from the authors experience within the field. Features examples from many industries, such as chemicals, plastics, oils, nuclear, food, drink, lighting, water and pharmaceuticals.

Preface
Why Bother to Design an Experiment?
Indroduction
Examples and Benefits
Develop a Better Product
Which Antiperspirant is Best?
A Complex Project
Good Design and Good Analysis
A Change for the Better - Significance Testing
Introduction
Towards a Darker Stout
Summary Statistics
The Normal Distribution
How Accurate is My Mean?
Is the New Additive an Improvement?
How Many Trials are Needed for an Experiment?
Were the Aims of the Investigation Achieved?
Problems
Improving Effectiveness Using a Paired Design
Introduction
An Example: Who Wears the Trousers?
How Do We Rate the Wear?
How Often Do You Carry Out an Assessment?
Choosing the Participants
Controlling the Participants
The Paired Design
Was the Experiment Successful?
Problems
A Simple but Effective Design for Two Variables
Introduction
An Investigation
Limitations of a One-Variable-at-a-Time Experiment
A Factorial Experiment
Confidence Intervals for Effect Estimates
What Conditions Should be Recommended?
Were the Aims of the Investigation Achieved?
Problems
Investigating 3 and 4 Variables in an Experiment
Introduction
An Experiment with Three Variables
The Design Matrix Method
Computation of Predicted Values
Computation of Confidence Interval
95% Confidence Interval for an Effect
95% Confidence Interval for a Predicted Value
Sequencing of the Trials
Were the Aims of the Experiment Achieved?
A Four-Variable Experiment
Half-Normal Plots
Were the Aims of the Experiment Achieved?
Problems
More for Even Less: Using a Fraction of a Full Design
Introduction
Obtaining Half-Fractional Designs
With Defining Contrast ABC
With Defining Contrast AC
Design of ½(24) Experiment
Analysing a Fractional Experiment
Summary 59
Did Wheelwright Achieve the Aims of His Experiment?
When and Where to Choose a Fractional Design
Three Variables
Four Variables
Five Variables or More
Problems
Saturated Designs
Introduction
Towards a Better Oil?
The Experiment
An Alternative Procedure for Estimating the Residual SD
Did Doug Achieve the Aims of His Experiment?
How Rugged is My Method?
Analysis of the Design
Conclusions from the Experiment
Did Serena Achieve Her Aims?
Which Order Should I Use for the Trials?
How to Obtain the Designs
Other Uses of Saturated Designs
Problems
Regression Analysis
Introduction
Example: Keeping Quality of Sprouts
How Good a Fit Has the Line to the Data?
Residuals
Percentage Fit
Correlation Coefficient
Percentage Fit - An Easier Method
Is There a Significant Relationship between the Variables?
Confidence Intervals for the Regression Statistics
Assumptions
Problem
Multiple Regression: The First Essentials
Introduction
An Experiment to Improve the Yield
Building a Regression Model
Selecting the First Independent Variable
Relationship between Yield and Weight
Model Building
Selecting the Second Independent Variable
An Alternative Model
Limitations to the Analysis
Was the Experiment Successful?
Problems
Designs to Generate Response Surfaces
Introduction
An Example: Easing the Digestion
Analysis of Crushing Strength
Analysis of Dissolution Time
How Many Levels of a Variable Should We Use in a Design?
Was the Experiment Successful?
Problem
Outliers and Influential Observations
Introduction
An Outlier in One Variable
Other Outlier Tests
Outliers in Regression
Influential Observations
Outliers and Influence in Multiple Regression
What to Do After Detection?
Central Composite Designs
Introduction
An Example: Design the Crunchiness
Estimating the Variability
Estimating the Effects
Using Multiple Regression
Second Stage of the Design
Has the Experiment Been Successful?
Choosing a Central Composite Design
Critique of Central Composite Designs
Designs For Mixtures
Introduction
Mixtures of Two Components
A Concrete Case Study
Design and Analysis for a 3-Component Mixture
Designs with Mixture Variables and Process Variables
Fractional Experiments
Was the Experiment Successful?
Computer-Aided Experimental Design (CAED)
Introduction
How It Works
An Example
Selecting the Repertoire
Selecting the Model and Number of Trials
How the Program Chooses the Design Set
Summary
Problems
Optimization Designs
Introduction
The Principles behind EVOP
EVOP: The Experimental Design
Running EVOP Programmes
The Principles of Simplex Optimization
Simplex Optimization: An Experiment
Comparison of EVOP, Simplex and Response Surface Methods
Number of Trials (Batches) Required
Production of In-Specification Product
Obtaining Optimum
Understanding Variables
Amount of Judgement Required
Coping with Nuisance Variables
Improving a Bad Experiment
Introduction
Was the Experiment Successful?
How to Compare Several Treatments
Introduction
An Example: Which is the Best Treatment?
Analysis of Variance
Multiple Comparison Test
Are the Standard Deviations Significantly Different?
Cochran's Test for Standard Deviations
When Should the Above Method Not be Used?
Was Golightly's Experiment Successful?
Problems
Experiments in Blocks
Introduction
An Example: Kill the Sweat
Analysis of the Data
Benefits of a Randomized Block Experiment
Was the Experiment Successful?
Double and Treble Blocking
Example: A Dog's Life
The Latin Square Design
Latin Square Analysis of Variance
Properties and Assumptions of the Latin Square Design
Examples of Latin Squares
Was the Experiment Successful?
An Extra Blocking Factor - Graeco-Latin Square
Problem
Two-Way Designs
Introduction
An Example: Improving the Taste of Coffee
Two-Way Analysis of Variance
Multiple Comparison Test
Was the Experiment Successful?
Problem
Too Much at Once: Incomplete Block Experiments
Introduction
Example: An Incomplete Block Experiment
Adjusted Means
Analysis of Variance for Balanced Incomplete Block Design
Alternative Designs
A Design with a Control
Was Jeremy's Experiment Successful?
Problem
23 Ways of Messing Up an Experiment
Introduction
23 Ways of Messing Up an Experiment
Initial Thoughts When Planning an Experiment
Developing the Ideas
Designing the Experiment
Conducting the Experiment
Analysing the Data
Summary
Solutions to Problems
Statistical Tables
Index
Table of Contents provided by Publisher. All Rights Reserved.

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Effective Experimentation For Scientists and Technologists

Summary

Author Biography

Table of Contents

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