The course will then turn on the relation between the population and the random sample and on how characteristics observed in the sample can be generalized to the population. Some elementary probability elements will be needed here. This will lead to the important concepts of standard error and confidence intervals (for means, proportions, odds ratios, hazard ratios). The general theory of hypothesis testing will be briefly outlined from an intuitive perspective and the fundamental concepts of statistical significance, power calculation and p-value will be introduced.
Then, we shall review some of the most frequently used testing procedures: correlation test, unpaired and paired t-tests for comparing two means values, analysis of variance for comparing several means (with multiple tests correction), chi-squared test (Fisher exact test) for comparing two proportions and more generally for contingency tables, McNemar test for paired proportions, and two-way analysis of variance for repeated data. The logistic model and Cox model will be briefly alluded to because of their importance in the medical literature. Finally, the basic principles underlying non parametric tests will be outlined and some of the most used distribution-free tests presented (Spearman correlation, Wilcoxon signed rank test, Mann-Whitney U-test, Kruskal-Wallis and Friedman tests).
You can apply until:
Always verify the dates on the programme website.
Prof. Adelin Albert, PhD
This programme may require students to demonstrate proficiency in English.
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
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