The last decades a debate has been going on about the use of hypothesis testing. This has led some teachers to think that confidence intervals and effect sizes need to be taught instead of formal hypothesis testing with p-values. Although we see shortcomings of the use of p-values in statistical inferences and the difficulties in really understanding hypothesis tests, we take a different view. We think that it is essential to understand what the fundamental principles are behind hypothesis testing in order to obtain correct statistical inference by interpreting confidence intervals (and, at the same time, p-values). In our course “Applied Statistics” for graduate students we designed course material in which we explain the three main approaches of hypothesis testing, Fisher, Neyman-Pearson and Bayesian, using a popular chance game as illustration. In this paper, we will shortly present the highlights of the course material, the results of the evaluation of our teaching, and suggestions for extensions.
|Subtitel||Sustainability in statistics education|
|Redacteuren||Katie Makar, Bruno de Sousa, Robert Gould|
|Status||Published - jul-2014|
|Evenement||Sustainability in statistics education - ICOTS-9, Flagstaff, Arizona, United States|
Duur: 13-jul-2014 → 18-jul-2014
|Conference||Sustainability in statistics education|
|Periode||13/07/2014 → 18/07/2014|