Probability and Statistics for Engineering and the Sciences with Modeling using R
eBook - ePub

Probability and Statistics for Engineering and the Sciences with Modeling using R

  1. 410 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Probability and Statistics for Engineering and the Sciences with Modeling using R

About this book

Probability and statistics courses are more popular than ever. Regardless of your major or your profession, you will most likely use concepts from probability and statistics often in your career.

The primary goal behind this book is offering the flexibility for instructors to build most undergraduate courses upon it. This book is designed for either a one-semester course in either introductory probability and statistics (not calculus-based) and/or a one-semester course in a calculus-based probability and statistics course.

The book focuses on engineering examples and applications, while also including social sciences and more examples. Depending on the chapter flows, a course can be tailored for students at all levels and background.

Over many years of teaching this course, the authors created problems based on real data, student projects, and labs. Students have suggested these enhance their experience and learning. The authors hope to share projects and labs with other instructors and students to make the course more interesting for both.

R is an excellent platform to use. This book uses R with real data sets. The labs can be used for group work, in class, or for self-directed study. These project labs have been class-tested for many years with good results and encourage students to apply the key concepts and use of technology to analyze and present results.

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Yes, you can access Probability and Statistics for Engineering and the Sciences with Modeling using R by William P. Fox,Rodney X. Sturdivant in PDF and/or ePUB format, as well as other popular books in Mathematics & Mathematics General. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Cover
  2. Half Title
  3. Series
  4. Title
  5. Copyright
  6. Dedication
  7. Contents
  8. Preface
  9. Acknowledgments
  10. 1 Introduction to Statistical Modeling and Models and R
  11. 2 Introduction to Data
  12. 3 Statistical Measures
  13. 4 Classical Probability
  14. 5 Discrete Distributions
  15. 6 Continuous Probability Models
  16. 7 Other Continuous Distribution (Some Calculus Required): Triangular, Unnamed, Beta, Gamma
  17. 8 Sampling Distributions
  18. 9 Estimating Parameters
  19. 10 One Sample Hypothesis Testing
  20. 11 Inferences Based on Two Samples
  21. 12 Reliability Modeling (Modified and Adapted from Military Reliability Modeling by Fox and Horton)
  22. 13 Introduction to Regression Techniques
  23. 14 Advanced Regression Models: Nonlinear, Sinusoidal, and Binary Logistics Regression Using R
  24. 15 ANOVA in R
  25. 16 Two-Way ANCOVA Using R
  26. Appendix A Labs/Projects
  27. Appendix B Answers to Selected Exercises
  28. Index