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Stephen B. Vardeman & J. Marcus Jobe

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Open Textbooks
Description
In Basic Engineering Data Collection and Analysis, Stephen B. Vardeman and J. Marcus Jobe stress the practical over the theoretical. Step by step, students get real engineering data and scenario examples along with chapter-long case studies that illustrate concepts in realistic, thoroughly detailed situations. This approach encourages students to work through the material by carrying out data collection and analysis projects from problem formulation through the preparation of professional technical reports—just as if they were on the job. Additional materials, including data sets and formula sheets, are available in the Chapters dropdown menu below.

• Details

  Published	Published By	Pages	ISBN	DOI	Chapters
  Jan. 12, 2023	Iowa State University Digital Press	851	978-1-958291-03-0	10.31274/isudp.2023.127	16
  License Information
  © 2001 Stephen B. Vardeman and J. Marcus Jobe. Basic Engineering Data Collection and Analysis is available under a Creative Commons Attribution NonCommercial ShareAlike (CC BY-NC-SA) 4.0 International license. You may share and adapt the material, so long as you provide appropriate credit to the original authors, do not use the material for commercial purposes, and any adaptations or remixes of the material which you create are distributed under the same license as the original.

• Chapters

  Basic Engineering Data Collection and Analysis has the following chapters:

  • Preface
  • 1 Introduction
  • 2 Data Collection
  • 3 Elementary Descripive Statistics
  • 4 Describing Relationships Between Variables
  • 5 Probability: The Mathematics of Randomness
  • 6 Introduction to Formal Statistical Inference
  • 7 Inference for Unstructured Multisample Studies
  • 8 Inference for Full and Fractional Factorial Studies
  • 9 Regression Analysis—Inference for Curve- and Surface-Fitting
  • Appendix A: More on Probability and Model Fitting
  • Appendix B: Tables
  • Answers to Section Exercises
  • Index
  • Additional Materials: Data Sets
  • Additional Materials: Formula Sheets

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