Practical-Statistics/index.html at master · rbmetcalf/Practical-Statistics · GitHub

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                <h2 style="font-family:Arial;">Practical Statistics for Physics and Astronomy</h2>
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            <p> Nontrivial data analysis problems are frequently encountered in modern astronomy, cosmology and physics. They require an understanding of statistical methods, practical skills with software tools and sometimes some ingenuity that comes with experience. The student will gain a practical knowledge of statistical methods and software as applied to many example problems. Basic probability theory will be covered before learning about Bayesian and frequentest inference problems, Monte Carlo techniques, Fisher matrices, random fields, parameter estimation, non-parametric tests, hypothesis testing, and supervised and unsupervised classification and regression problems. The student will become familiar with current software in Python for analysing data and fitting models while getting an understanding of the theory behind them. </a> </p>
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