A Student's Guide to Data and Error Analysis

Part I. Data and Error Analysis: 1. Introduction 2. The presentation of physical quantities with their inaccuracies 3. Errors: classification and propagation 4. Probability distributions 5. Processing of experimental data 6. Graphical handling of data with errors 7. Fitting functions to data 8. Back to Bayes: knowledge as a probability distribution Answers to exercises Part II. Appendices: A1. Combining uncertainties A2. Systematic deviations due to random errors A3. Characteristic function A4. From binomial to normal distributions A5. Central limit theorem A6. Estimation of the varience A7. Standard deviation of the mean A8. Weight factors when variances are not equal A9. Least squares fitting Part III. Python Codes Part IV. Scientific Data: Chi-squared distribution F-distribution Normal distribution Physical constants Probability distributions Student's t-distribution Units.

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