40 Python Statistics For Data Science Resources

For an introduction to statistics, this tutorial with real-life examples is the way to go. The notebooks of this tutorial will introduce you to concepts like mean, median, standard deviation, and the basics of topics such as hypothesis testing and probability distributions. A fine way to start your stats learning, since it is inspired by the books "Think Bayes" and "Think Stats", which are two top recommendations that will come back below! If you're looking for books, you can try out this free book on computational statistics in Python, which not only contains an introduction to programming with Python, but also treats topics such as Markov Chain Monte Carlo, the Expectation-Maximization (EM) algorithm, resampling methods, and much more. Or you can buy this book by Thomas Haslwanter for a general introduction to common statistical tests, linear regression analysis and topics from survival analysis and Bayesian statistics. Note that this book does take life and medical sciences as an application area. Both of the above books already introduce you to more advanced statistics topics with Python too, as you can see. If you're a fan of videos, you should consider watching this tutorial on statistical data analysis with SciPy with Christopher Fonnesbeck, an Assistant Professor in the Department of Biostatistics at the Vanderbilt University School of Medicine.