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The Principles of Experimental Research
 
 

The Principles of Experimental Research, 1st Edition

 
The Principles of Experimental Research, 1st Edition,K Srinagesh,ISBN9780750679268
 
 
 

  

Butterworth-Heinemann

9780750679268

9780080497815

432

229 X 152

A concise introductory textbook on designing and conducting experiments for quantitative research

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Key Features

* Covers such essential fundamentals as "definitions," "quantification," and standardization of test materials

* Shows students and professionals alike how to plan an experiment—from how to frame a proper Hypothesis to designing an experiment to accurately reflect the nature of the problem to "designing with factors."

* Includes a separate section on the use of Statistics in Experimental Research, including overview of probability and statistics, as well as Randomization, Replication and Sampling, as well as proper ways to draw statistical inferences from experimental data.

Description

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.

Readership

Undergraduate and first-year graduate students in most engineering disciplines taking required or optional course in “Design of Experiments,” “Senior Design Project,” “Capstone Design Project,” “Engineering Statistics,” and other course related to experimental research, data analysis and statistical inference.

K Srinagesh

Affiliations and Expertise

Professor, Mechanical Engineering, University of Massachusetts, Dartmouth

The Principles of Experimental Research, 1st Edition

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
 
 
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