This book is a practical guide on how to analyze data and estimate errors. The necessary formulae for performing calculations are given, and the ideas behind them are explained, although this is not a formal text on statistics.
This book is a practical guide on how to analyze data and estimate errors. The necessary formulae for performing calculations are given, and the ideas behind them are explained, although this is not a formal text on statistics.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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.
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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