Seminar Slides | Multiple Comparisons and the False Discovery Rate | Dr. Saunak Sen
|Please click below for the slides from Dr. Saunak Sen’s presentation May 21st, 2019. Multiple Comparisons and the False Discovery Rate
Please click below for the slides from Dr. Saunak Sen’s presentation May 21st, 2019. Multiple Comparisons and the False Discovery Rate
Please see below for the sides from Dr. Sen’s seminar discussion. p-value-discussion
P-values: What they are and what they are not, will look in detail at good examples of using p-values and how to interpret them. After reviewing widely understood problems with p-values, attention is drawn to regularly encountered use of p-values where it is less clear what their correct interpretation actually is. Furthermore, we demonstrate why… Read More
The American Statistical Association (ASA) has released a “Statement on Statistical Significance and P-Values” with six principles underlying the proper use and interpretation of the p-value. The ASA releases this guidance on p-values to improve the conduct and interpretation of quantitative science and inform the growing emphasis on reproducibility of science research. The statement also… Read More
With the many problems that p-values have, and the temptation to “bless” research when the p-value falls below an arbitrary threshold such as 0.05 or 0.005, researchers using p-values should at least be fully aware of what they are getting. They need to know exactly what a p-value means and what are the assumptions required… Read More