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.
This website uses Google Analytics. By clicking on "I accept" or by navigatin on it, you authorize us to deposit a cookie for audience measurements purposes.
You have accepted the deposit of audience measurement cookies in your navigator.
You have declined the deposit of audience measurement cookies in your navigator.
"Do Not Track" is enabled in your browser. You cannot allow statistics collection.
