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Experimental statistics and data analysis for mechanical and aerospace engineers /

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Bibliographic Details
Main Author: Middleton, James A. (Author)
Corporate Author: EBSCOhost
Format: eBook
Language:English
Published: Boca Raton, FL : CRC Press, Taylor & Francis Group, 2022.
Edition:First edition.
Series:Advances in applied mathematics.
Subjects:
Engineering > Statistical methods.
Engineering > Data processing.
MATHEMATICS > Probability & Statistics > General.
SCIENCE > Applied Sciences.
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Cover
  • Half Title
  • Series Page
  • Title Page
  • Copyright Page
  • Dedication
  • Contents
  • Preface
  • List of Figures
  • List of Tables
  • Symbols
  • I
  • 1. Introduction
  • 1.1. Approach of This Book
  • 1.1.1. Data Modeling
  • 1.1.2. Building an Empirical Mindset
  • 1.2. The Role of Data
  • 1.3. References
  • 1.4. Chapter 1 Study Problems
  • 2. Dealing with Variation
  • 2.1. Measurement
  • 2.1.1. Natural Variation
  • 2.1.1.1. Shape of Data
  • 2.2. Distribution
  • 2.2.1. Histogram
  • 2.2.1.1. How to Draw a Histogram
  • 2.2.1.2. Comparing Histograms
  • 2.3. Accuracy and Precision of Measurements
  • 2.3.1. Accuracy-Systematic Error
  • 2.3.1.1. Sources of Systematic Error
  • 2.3.2. Precision-Random Error
  • 2.4. Continuous Versus Discrete Data
  • 2.4.1. Discrete Random Variables
  • 2.4.2. Continuous Random Variables
  • 2.5. Law of Large Numbers
  • 2.6. Central Limit Theorem
  • 2.7. Representativeness
  • 2.7.1. "Simple" Random Sampling
  • 2.8. References
  • 2.9. Chapter 2 Study Problems
  • 3. Types of Data
  • 3.1. Scales of Measure
  • 3.1.1. Nominal Data
  • 3.1.2. Ordinal Data
  • 3.1.3. Interval Data
  • 3.1.4. Ratio Data
  • 3.2. Population Parameters and Sample Statistics
  • 3.2.1. Parameters
  • 3.2.1.1. Population Parameters
  • 3.2.1.2. What Are the Important Sample Statistics That Model Population Parameters?
  • 3.2.1.3. Nominal Data:
  • 3.2.1.4. Symmetry of the Binomial Distribution
  • 3.2.1.5. Ordinal Data:
  • 3.2.1.6. Interval
  • 3.3. The Sample Mean and Standard Deviation as Robust Estimators
  • 3.4. References
  • 3.5. Study Problems for Chapter 3
  • 4. Introduction to Probability
  • 4.1. Simple Probability
  • 4.2. Conditional Probability
  • 4.3. Moments of a Distribution
  • 4.3.1. The Mean as a Moment
  • 4.3.2. The Variance as a Moment
  • 4.3.3. Summary: Bringing Probability, Moments, and Sample Statistics
  • 4.4. Probability Density Function and Cumulative Distribution
  • 4.5. Summary of Probability
  • 4.6. Study Problems for Chapter 4
  • 5. The Sampling Distribution of the Mean
  • 5.1. The General Logic of the Sampling Distribution
  • 5.2. Sampling Distribution of the Mean
  • 5.3. The Standard Normal Distribution
  • 5.3.1. Probability Density of the Standard Normal Distribution
  • 5.3.2. Now Let's Do Some Real Stats with the Normal Distribution!
  • 5.3.3. The Z-test
  • 5.4. Summary
  • 5.5. References
  • 5.6. Study Problems for Chapter 5
  • II. Testing Hypotheses
  • 6. The Ten Building Blocks of Experimental Design
  • 6.0.1. Notation
  • 6.1. Basic Experimental Designs
  • 6.1.1. One-shot Case Study
  • 6.1.2. One-sample, Pre-post Design
  • 6.1.3. Static Sample Comparison
  • 6.1.4. Random Sample Design
  • 6.1.5. Pre-post Randomized Sample
  • 6.1.6. Factorial Designs
  • 6.1.7. Randomized Block Factorial Designs
  • 6.1.8. One-shot Repeated Measures
  • 6.1.9. Randomized Factors Repeated Measures
  • 6.1.10. Ex-post-facto
  • 6.1.11. Time Series
  • 6.2. Summary
  • 6.3. References.