Objectives of Programme's Learning Outcomes

• 1. Pharmaceutical expertise: Use a foundation of concepts and knowledge in health sciences and pharmaceutical sciences.
• Understand and apply mathematical translations of large models and chemical and/or biological phenomena through abstract reasoning
• Understand and use different graphical representations of numerical values and their relationships
• 2. Scientific method: Solve pharmaceutical problems using their knowledge and critical mind.
• Understand and apply the basic principles of reasoning (obtaining data, analysis, synthesis, comparison, the rule of three, syllogism, analogy, Boolean logic, etc.)
• Understand and use statistical methods
• Use a hypothesis in inductive, deductive or abductive reasoning
• Develop a critical, practical and analytical mind
• Manage doubt and uncertainty
• Develop and rigorously manage an experimental protocol (from information gathering to the production, interpretation and presentation of results).
• 5. Quality: Assess themself, expand their knowledge and adapt their attitude.
• Research, read, interpret, and critique a scientific paper with sufficient knowledge of scientific English

Learning Outcomes of UE

At the end of this course, students will be able to :
- Understand basic principles of statistical hypothesis tests
- Understand basic tools used to assess normality of a distribution
- Compare central tendencies of two or more than two groups
- Compare proportions, use statistical tests of significance and compute odds ratios and related tools
- Analyze the relationship between quantitative variables : tests for linear correlation, linear regression analysis
- Understand basic principles of diagnostic tools used in medicine, and principles of Bayesian reasoning

UE Content: description and pedagogical relevance

Basics of statistical hypothesis test : null and alternative hypothesis; unilateral and bilateral tests; power of a test : concept and uses in medicine; number of subjects to include in a trial : basics and practical applications
Tests assessing the normality of a distribution : Shapiro-Wilk and Kolmogorov-Smirnov tests; uses and practical examples; graphical methods including QQ plots; data transformations
Comparisons of two means : uses; Z-test; Student t test; Fisher's test for comparison of two variances; Welch's test; Mann-Whitney and Wilcoxon tests; tests in case of paired samples : paired t-test and Wilcoxon paired test
Comparisons of two proportions : uses; relative risk and odds ratio; confidence interval of an odds ratio; contingency tables; chi2 tests and related tests (Yates correction, Mc Nemar); Fisher's exact test
Comparisons of more than two sample means : uses; one-way ANOVA : basics, ANOVA table; homoscedasticity, interpretation of the results of an ANOVA test; non parametric approaches (Kruskal-Wallis and Friedman)
Linear correlation : how to compute r and its confidence interval (Fisher's transformations); tests on r; test on the slope of the linear regression
Diagnostic tests and introduction to Bayesian reasoning.