Practical Guide to Data Analysis for Physical Science Students

About this book

Practical guide on how to analyse data and estimate errors.

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.

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