Today's students need to understand many basic data-handling methods in order to make effective use of the powerful computer programs that are now widely available for analyzing and reducing experimental data. The third edition of Data Reduction and Error Analysis for The Physical Sciences provides a detailed introduction to statistical analysis, data modeling, and least squares fitting as they are applied to experiemental research. It includes a through treatment of techniques for fitting data by the method of least squares , beginning with simple linear fitting procedures and continuing through more complex methods for making non-linear fits.An introduction to data simulation by the Monte Carlo technique is also included. The Level in appropriate for undergraduates and introductory graduate students. No previous background in statistics is required.
Preface to The Third Edition
Chapter 1 : Uncertainties in Measurements
Chapter 2 : Probability Distributions
Chapter 3 : Error Analysis
Chapter 4 : Estimates of Mean and Errors
Chapter 5 : Monte Carlo Techniques
Chapter 6 : Least-Squares Fit to a Straight Line
Chapter 7 : Least-Squares Fit to a Polynomial
Chapter 8 : Least-Squares Fit to an Arbitrary Function
Chapter 9 : Fitting Composite Curves
Chapter 10 : Direct Application of the Maximum-Likelihood Method
Chapter 11 : Testing The Fit
Appendix A : Numerical Methods
Appendix B : Matrices
Appendix C : Graphs and Tables
Appendix D : Histograms and Graphs
Appendix E : Computer Routines in Fortran
References
Answers to Selected Exercises
Index
