The aim of this course is to teach you how to perform basic statistical analysis using R. First we review the foundations (sampling theory, discrete and continuous distributions), then we focus on classical hypothesis testing. This course will refresh and improve your generic statistics knowledge. It is highly recommended for new PhD students, but we welcome everyone thirsting for knowledge.
Topics in detail:
- Sampling theory: obtaining information about a population via sampling. Sample characteristics (location, dispersion, skewness), estimation of the mean, standard error of the mean.
- Discrete and continuous probability distributions. Central limit theorem.
- Hypothesis testing. Basic principles, one- and two-sided testing, types of errors, power calculations.
- "Cookbook of tests": location testing, normality, variance comparisons, counting statistics, contingency tables, regression tests.
Please note that this course will not teach you bioinformatics. We discuss generic statistical concepts only.
Registration
