Planning and Executing Credible Experiments. Robert J. Moffat
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Table of Contents
1 Cover
6 Preface Audience Accompanying Material Recommended Companion Texts
9 1 Choosing Credibility 1.1 The Responsibility of an Experimentalist 1.2 Losses of Credibility 1.3 Recovering Credibility 1.4 Starting with a Sharp Axe 1.5 A Systems View of Experimental Work 1.6 In Defense of Being a Generalist References Homework
10 2 The Nature of Experimental Work 2.1 Tested Guide of Strategy and Tactics 2.2 What Can Be Measured and What Cannot? 2.3 Beware Measuring Without Understanding: Warnings from History 2.4 How Does Experimental Work Differ from Theory and Analysis? 2.5 Uncertainty 2.6 Uncertainty Analysis References Homework
11 3 An Overview of Experiment Planning 3.1 Steps in an Experimental Plan 3.2 Iteration and Refinement 3.3 Risk Assessment/Risk Abatement 3.4 Questions to Guide Planning of an Experiment Homework
12 4 Identifying the Motivating Question 4.1 The Prime Need 4.2 An Anchor and a Sieve 4.3 Identifying the Motivating Question Clarifies Thinking 4.4 Three Levels of Questions 4.5 Strong Inference 4.6 Agree on the Form of an Acceptable Answer 4.7 Specify the Allowable Uncertainty 4.8 Final Closure Reference Homework
13 5 Choosing the Approach 5.1 Laying Groundwork 5.2 Experiment Classifications 5.3 Real or Simplified Conditions? 5.4 Single‐Sample or Multiple‐Sample? 5.5 Statistical or Parametric Experiment Design? 5.6 Supportive or Refutative? 5.7 The Bottom Line References Homework
14 6 Mapping for Safety, Operation, and Results 6.1 Construct Multiple Maps to Illustrate and Guide Experiment Plan 6.2 Mapping Prior Work and Proposed Work 6.3 Mapping the Operable Domain of an Apparatus 6.4 Mapping in Operator's Coordinates 6.5 Mapping the Response Surface
15 7 Refreshing Statistics 7.1 Reviving Key Terms to Quantify Uncertainty 7.2 The Data Distribution Most Commonly Encountered The Normal Distribution for Samples of Infinite Size 7.3 Account for Small Samples: The t‐Distribution 7.4 Construct Simple Models by Computer to Explain the Data 7.5 Gain Confidence and Skill at Statistical Modeling Via the R Language 7.6 Report Uncertainty 7.7 Decrease Uncertainty (Improve Credibility) by Isolating Distinct Groups