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<title>Lecture Notes - Practical Statistics</title>
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<h1 style="font-family:Fantasy;"> <a href="index.html"> Practical Statistics </a> </strong> </h1>
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<h2>Lecture Topics </h2>
<ol>
<li> Fundimental properties of probability . </li>
<li> Random Variables. </li>
<li> Classic probability distributions. </li>
<li> Bayesian parameter estimation and model selection. </li>
<li> Frequentist hypotheses testing. </li>
<li> Fisher matrices. </li>
<li> Non-parametric tests. </li>
<li> Random Fields. </li>
<li> Image reconstruction and map making. </li>
<li> Numerical methods for the Bayesian Inference problem. </li>
<li> supervised and unsupervised machine learning methods for classification. </li>
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<h2> Lecture Notes </h2>
<p> The current version of the notes is available <a href="lecturenotes/notes.pdf" target="_blanck"> here </a> which has a table of contents. They will be regularly updated. </p>
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