The need to understand how to design and set up an investigative experiment is nearly universal to all students in engineering, applied technology and science, as well as many of the social sciences. Many schools offer courses in this fundamental skill and this book is meant to offer an easily accessible introduction to the essential tools needed, including an understanding of logical processes, how to use measurement, the do’s and don’ts of designing experiments so as to achieve reproducible results and the basic mathematical underpinnings of how data should be analyzed and interpreted. The subject is also taught as part of courses on Engineering statistics, Quality Control in Manufacturing, and Senior Design Project, in which conducting experimental research is usually integral to the project in question.

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## Table of Contents

1 Experimental Research in Science: Its Name and Nature

1.1 Defining Science

1.2 Science: Play or Profession

1.3 Science and Research

1.4 Varieties of Experimental Research

1.5 Conventional Researchers

1.6 Bibliography

2 The Importance of Definitions

2.1 Toward Definition

2.2 Defining “Definition”

2.3 Common Terms Used in Definitions

2.4 Varieties of Definitions

2.4.1 A. Direct and B. Indirect Definitions

2.4.2 C. Informal and D. Formal Definitions

2.4.3 E. Lexical and F. Stipulated Definitions

2.4.4 G. Nominal and H. Real Definitions

2.4.5 J. Definitions by Denotation

2.4.6 K. Ostensive Definitions

2.4.7 L. Definitions by Genus and Difference

2.5 Need for Definitions

2.6 What Definitions Should and Should Not Do

2.7 References

2.8 Bibliography

3 Aspects of Quantification

3.1 Quantity and Quality

3.2 The Uses of Numbers

3.3 An Intellectual Close-up of Counting

3.4 The Process of Measurement

3.5 Quantities and Measurements

3.6 Derived Quantities

3.7 Units for Measurement

3.8 Fundamental Quantities and Dimensions

3.9 Dimensional Analysis

3.10 Accuracy versus Approximation

3.11 Bibliography

4 The Purpose and Principles Involved in Experimenting

4.1 The Purpose of Experimenting

4.2 Cause and Effect

4.3 Pertinence and Forms of Cause

4.4 Mill’s Methods of Experimental Inquiry

4.4.1 Method of Agreement

4.4.2 Method of Difference

4.4.3 Joint Methods of Agreement and Difference

4.4.4 Method of Residue

4.4.5 Method of Concomitant Variation

4.5 Planning for the Experiment

4.6 Standardization of Test Material(s)

4.7 Reproducibility

4.8 Number of “Experiments”

4.9 References

4.10 Bibliography

Part II: Planning the Experiments

5 Defining the Problem for Experimental Research

5.1 To Define a Problem

5.2 Relation of the Problem to Resources

5.3 Relevance of the Problem

5.4 Extent of the Problem

5.5 Problem: Qualitative or Quantitative?

5.6 Can the Problem Be Reshaped?

5.7 Proverbs on Problems

5.8 At the beginning

5.9 In Progress

5.10 At the End

5.11 References

5.12 Bibliography

6 Stating the Problem as a Hypothesis

6.1 The Place of Hypothesis in Research

6.2 Desirable Qualities of Hypotheses

6.3 Bibliography

7 Designing Experiments to Suit Problems

7.1 Several Problems, Several Causes

7.2 Treatment Structures

7.2.1 Placebo

7.2.2 Standard Treatment

7.2.3 “Subject-and-Control” Group Treatment

7.2.4 Paired Comparison Treatment

7.2.5 Varying the Amount of One of the Two Factors

7.3 Many Factors at Many Levels, but One Factor at a Time

7.4 Factorial Design, the Right Way

7.5 Too Many Factors on Hand?

7.6 “Subjects-and-Controls” Experiments

7.6.1 Varieties within Subjects and Controls: Paired Comparison

Design

7.6.2 Experiments with Humans

7.7 Combined Effect of Many Causes

7.8 Unavoidable (“Nuisance”) Factors

7.9 Bibliography

8 Dealing with Factors

8.1 Designing Factors

8.2 Experiments with Designed Factors

8.3 Matrix of Factors

8.3.1 More Than Three Factors

8.4 Remarks on Experiments with Two-Level Factors

8.5 Response of Multifactor Experiments

8.6 Experiments with More Factors, Each at Two Levels

8.7 Fractional Factorials

8.8 Varieties of Factors

8.8.1 Quantitative versus Qualitative Factors

8.8.2 Random versus Fixed Factors

8.8.3 Constant and Phantom Factors

8.8.4 Treatment and Trial Factor

8.8.5 Blocking and Group Factors

8.8.6 Unit Factor

8.9 Levels of Factors

8.9.1 Levels of Quantitative Factors

8.9.2 Levels of Qualitative Factors

8.10 Bibliography

9 Factors at More Than Two Levels

9.1 Limitations of Experiments with Factors at Two Levels

9.2 Four-Level Factorial Experiments

9.2.1 Main Effects and Interactions

9.3 Interactions

9.4 Main Effects

9.5 More on Interactions

9.6 More Factors at More Than Two Levels

9.6.1 Fractional Factorial with Three-Level Factors

9.7 Bibliography

Part III: The Craft Part of Experimental Research

10 Searching through Published Literature

10.1 Researcher and Scholar

10.2 Literature in Print

10.3 Overdoing?

10.4 After the Climb

10.5 Bibliography

11 Building the Experimental Setup

11.1 Diversity to Match the Need

11.2 Designing the Apparatus

11.2.1 Seeking Advice

11.3 Simplicity, Compactness, and Elegance

11.4 Measuring Instruments

11.5 Calibration

11.6 Researcher as Handyman

11.7 Cost Considerations

11.8 Bibliography

Part IV: The Art of Reasoning in Scientific Research

12 Logic and Scientific Research

12.1 The Subject, Logic

12.2 Some Terms in Logic

12.3 Induction versus Deduction

12.4 References

12.5 Bibliography

13 Inferential Logic for Experimental Research

13.1 Inferential Logic and Experimental Research

13.2 Logical Fallacies

13.2.1 Fallacies of Ambiguity

13.2.2 Fallacies of Irrelevance

13.3 Argument

13.3.1 Categorical Propositions

13.3.2 Forms of Categorical Propositions

13.3.3 Conventions, Symbolism, and Relations among Categorical

Propositions

13.4 Diagrammatic Representation of [AQ: Categorical?]Propositions

13.5 Categorical Syllogisms

13.5.1 Structures of Syllogisms

13.5.2 Validity of Syllogisms

13.5.3 Venn Diagrams for Testing Syllogisms

13.6 Ordinary Language and Arguments

13.7 References

13.8 Bibliography

14 Use of Symbolic Logic

14.1 The Need for Symbolic Logic

14.2 Symbols in Place of Words

14.3 Conjunction

14.4 Truth Tables

14.5 Disjunction

14.6 Negation

14.7 Conditional Statements

14.8 Material Implication

14.9 Punctuation in Symbolic Logic

14.10 Equivalence: “Material” and “Logical”

14.10.2 Logical Equivalence

14.11 Application of Symbolic Logic

14.11.1 Ordinary Language to Symbolic Language

14.12 Validity of Arguments

14.13 Reference

14.14 Bibliography

Part V: Probability and Statistics for Experimental Research

15 Introduction to Probability and Statistics

15.1 Relevance of Probability and Statistics in Experimental Research

15.2 Defining the Terms: Probability and Statistics

15.2.1 Probability

15.2.2 Statistics

15.3 Relation between Probability and Statistics

15.4 Philosophy of Probability

15.5 Logic of Probability and Statistics

15.6 Quantitative Probability

15.6.1 Relative Frequency Theory

15.7 Nature of Statistics

15.8 Measures of Central Tendency (Average)

15.8.1 Arithmetic Average (Sample Mean)

15.8.2 Weighted Mean

15.8.3 Median

15.8.4 Mode

15.9 Measures of Dispersion

15.9.1 Range

15.9.2 Mean Deviation

15.9.3 Coefficient of Dispersion

15.9.4 Standard Deviation

15.10 Tabular Presentations of Statistical Data

15.11 Grouping the Data

15.12 Graphical Presentations of Data

15.12.1 Histogram

15.12.2 Frequency Polygon

15.12.3 Cumulative Frequency Distribution

15.13 Normal Distribution Curve

15.14 Frequency Distributions That Are Not Normal

15.15 References

15.16 Bibliography

16 Randomization, Replication, and Sampling

16.1 Need for Randomization

16.2 Applications of Randomization

16.3 Methods of Randomization

16.4 Meaning of Randomization

16.5 Replication

16.6 Samples and Sampling

16.7 Notions of Set

16.8 Permutations and Combinations

16.8.1 Permutations

16.8.2 Combinations

16.9 Quantitative Statement of Randomization

16.10 Sampling Methods

16.10.1 Simple Random Sampling

16.10.2 Cluster Sampling

16.10.3 Stratified Sampling

16.10.4 Systematic Sampling

16.10.5 Multistage Sampling

16.11 Bibliography

17 Further Significance of Samples

17.1 Inference from Samples

17.2 Theoretical Sampling Distribution of X

17.3 Central Limit Theorem

17.4 Standard Normal Distribution

17.5 Frequency Distribution and Probability Function

17.6 Standard Normal Curve

17.7 Questions/Answers Using the APSND Table

17.8 Bibliography

18 Planning the Experiments in Statistical Terms

18.1 Guiding Principles

18.2 Some Preliminaries for Planned Experiments

18.2.1 Sample Size

18.2.2 Minimum Acceptable Improvement

18.3 Null and Alternate Hypotheses

18.3.1 Null Hypothesis in an Experiment

18.3.2 Alternate Hypothesis

18.3.3 Risks Involved: a and b Errors

18.3.4 Sample Mean X: Its Role in the Design

18.3.5 Hypotheses Based on Other Parameters

18.4 Accepting (or Rejecting) Hypotheses: Objective Criteria

18.5 Procedures for Planning the Experiments

18.5.1 Criterion Values

18.6 Other Situation Sets

18.7 Operating Characteristic Curve

18.8 Sequential Experimenting

18.9 Concluding Remarks on the Procedures

18.10 Bibliography

19 Statistical Inference from Experimental Data

19.1 The Way to Inference

19.2 Estimation (From Sample Mean to Population Mean)

19.2.1 Interval Estimation

19.2.2 Variations in Confidence Interval

19.2.3 Interval Estimation of Other Parameters

19.3 Testing of Hypothesis

19.4 Regression and Correlation

19.4.1 Regression Analysis

19.4.2 Measuring the Goodness of Regression

19.4.3 Correlation Coefficient

19.5 Multiple Regression

19.6 Bibliography

## Product details

- ASIN : B011MDN19K
- Publisher : Butterworth-Heinemann; 1st edition (January 1, 1709)

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