Mathematical Statistics for Physicists

<p>An introduction to probability and statistics with applications.</p><p>The course is intended to give the student the basics in mathematical modelling of random variation and an understanding of the principles behind statistical analysis. It shall also give the students a toolbox containing the most commonly used models and methods, as well as the ability to use these in practical situations.</p> <p>The course fills two purposes, providing a fundamental knowledge of mathematical statistics, as well as giving a foundation for further studies.</p> <p>The fundamental knowledge is essential for those who, in their professional lives, will not necessarily be involved in statistical analyses on a daily basis, but who, on occasion, will be expected to perform basic statistical tests and present the results to their colleagues. They will also be expected to be able to read and assess the analyses of others.</p> <p>The course shall also give a basis for further studies, both in probability theory and inference theory, as well as in the application areas.</p> <p>The course treats:</p> <p>Bayes theorem. Expectation and variance. Normal distribution binomial distribution, and other important distributions for measurements and frequencies. Data analysis. Statistical inference:</p> <p>Point estimates. Interval estimates and hypothesis testing. Methods for normally distributed observations. Approximative methods based on the normal distribution. Comparisons between expectations. Variability, and distributions. Estimates of proportions. Regression analysis and calibration. Covariance och correlation. Correlation between two explanatory variables. Examples are chosen with respect to the different programs.</p>