Cours magistraux 1- What is a variable? 2- What is a variance? 3- What is chance (for a statistician)? 4- What is a data distribution? 5- What is an (experimental) factor? 6- What is a variance model? 7- What is an experimental design? 8- What is decision making (for a statistician)? 9- What is a decision risk? 10- What is a false positive and a false negative? 11- How to control the power of a statistical test? Travaux Dirigés 1- What is measured in Biology? Why do repetitions? Determinism versus stochastics in Biology. Knowing without knowing everything. 2- Or how and why to quantify how much an average varies over a set of repetitions. 3- Distinguishing what is due to chance from what is unknown. Difference between artifact and measurement error. 4- Why look at this? Example of the 6-sided dice and "hands-on" demonstration of the central limit theorem. To bring back to a Normal distribution. 5- Difference between what we measure and what we study. The case of co-variables. 6- Or why look for an abstract representation of what we study empirically. 7- "What is well conceived is clearly stated... » 8- Certainty and completeness, limits or fantasies? How can we never be wrong in statistics (or why do we always get it wrong... but by how much?). 9- The risk of the first kind. But what if we are wrong in the first degree? 10- Why and which category to try to control. 11- Repetitions, multiple tests; limits and necessities.
