Thomas Haslwanter is a Professor at the Department of Medical Engineering of the University of Applied Sciences Upper Austria in Linz, and lecturer at the ETH Zurich in Switzerland. He also worked as a researcher at the University of Sydney, Australia and the University of Tuebingen, Germany. He has extensive experience in medical research, with a focus on the diagnosis and treatment of vertigo and dizziness and on rehabilitation. After 15 years of extensive use of Matlab, he discovered Python, which he now uses for statistical data analysis, sound and image processing, and for biological simulation applications. He has been teaching in an academic environment for more than 10 years.
Table of Contents
Part I: Python and Statistics.- Why Statistics?.- Python.- Data Input.- Display of Statistical Data.-
Part II: Distributions and Hypothesis Tests.- Background.- Distributions of One Variable.- Hypothesis Tests.- Tests of Means of Numerical Data.- Tests on Categorical Data.- Analysis of Survival Times.-
Part III: Statistical Modelling.- Linear Regression Models.- Multivariate Data Analysis.- Tests on Discrete Data.- Bayesian Statistics.- Solutions.- Glossary.-
Index.