9780521414159

A Practical Guide to Data Analysis for Physical Science Students

by
  • ISBN13:

    9780521414159

  • ISBN10:

    0521414156

  • Format: Hardcover
  • Copyright: 1991-11-29
  • Publisher: Cambridge University Press
  • Purchase Benefits
  • Free Shipping On Orders Over $35!
    Your order must be $35 or more to qualify for free economy shipping. Bulk sales, PO's, Marketplace items, eBooks and apparel do not qualify for this offer.
  • Get Rewarded for Ordering Your Textbooks! Enroll Now
List Price: $104.00 Save up to $62.00
  • Buy New
    $100.88
    Add to Cart Free Shipping

    SPECIAL ORDER: 1-2 WEEKS

Supplemental Materials

What is included with this book?

  • The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any access cards, study guides, lab manuals, CDs, etc.
  • The eBook copy of this book is not guaranteed to include any supplemental materials. Typically, only the book itself is included. This is true even if the title states it includes any access cards, study guides, lab manuals, CDs, etc.

Summary

This textbook is intended for undergraduates who are carrying out laboratory experiments in the physical sciences for the first time. It is a practical guide on how to analyze data and estimate errors. The necessary formulas for performing calculations are given, and the ideas behind them are explained, although this is not a formal text on statistics. Specific examples are worked through step by step in the text. Emphasis is placed on the need to think about whether a calculated error is sensible. Students should take this book with them to the laboratory, and the format is intended to make this convenient. The book will provide the necessary understanding of what is involved, should inspire confidence in the method of estimating errors, and enable numerical calculations without too much effort.

Table of Contents

Preface
Glossary
1. Experimental errors
1.1. Why estimate errors?
1.2. Random and systematic errors
1.3. Distributions
1.4. Mean and variance
1.5. Gaussian distribution
1.6. The meaning of s
1.7. Combining errors
1.8. Systematic errors
1.9. An example including random and systematic errors
1.10. Combining results of different experiments
1.11. Worked examples
1.12. Does it feel right?
2. Least squares fitting
2.1. What are we trying to do
2.2. Weighted sum of squares
2.3. Determining the parameters
2.4. The error on the gradient and the intercept
2.5. Other examples
2.6. Observed numbers
2.7. Parameter testing
2.8. Distribution testing
2.9. Worked example of a straight line fit
2.10. Summary of straight line fitting
Problems
Appendices.

Rewards Program

Write a Review