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.
* 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.
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2 The Importance of Definitions
3 Aspects of Quantification
4 The Purpose and Principles Involved in Experimenting
Part II: Planning the Experiments
5 Defining the Problem for Experimental Research
6 Stating the Problem as a Hypothesis
7 Designing Experiments to Suit Problems
8 Dealing with Factors
9 Factors at More Than Two Levels
Part III: The Craft Part of Experimental Research
10 Searching through Published Literature
11 Building the Experimental Setup
Part IV: The Art of Reasoning in Scientific Research
12 Logic and Scientific Research
13 Inferential Logic for Experimental Research
14 Use of Symbolic Logic
Part V: Probability and Statistics for Experimental Research
15 Introduction to Probability and Statistics
16 Randomization, Replication, and Sampling
17 Further Significance of Samples
18 Planning the Experiments in Statistical Terms
19 Statistical Inference from Experimental Data