A Practical Guide to Data Analysis for Physical Science Students Book

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.