Unterschiede

Hier werden die Unterschiede zwischen zwei Versionen angezeigt.

--- wm18:pgwm18 [2018/07/15 20:37] – [Conclusion] admin
+++ wm18:pgwm18 [2018/07/15 20:43] – [Conclusion] admin
@@ Zeile 123: / Zeile 123: @@
 ==== Conclusion ====
-It is hard - maybe even impossible - to judge, which is the best prediction model. First of all, the data number is rather small, we have 16 predictions for the group stage and 15 predictions for the knockout stage, altogether $N=31$.
+It is hard to judge, which is the best prediction model. First of all, the data number is rather small. We have 16 predictions for the group stage and 15 predictions for the knockout stage, altogether $N=31$. Second, there is not a single criterion for //What is best?// If we chose the correct prediction of World Champion, then **NOB** is the best. But this criterion is too coarse. A bit better might be the number of correct predictions of qualification (**CP**). In this case, the best prediction is done by **GOP,NOB** and **SUD** (CP=20). But keep in mind, a single match that goes differently by a single penalty, like Spain against Russia can turn the whole ranking. Therefore, also the number of correct predictions is not suitable, it just a sidemark. If we use the prediction score, every prediction takes into account. But even in this case, the decision might not be as clear as one might think. The group stage is significantly different from the knockout stage.
-Second, there is not a single criteria for //What is best?//. If we chose simply the correct prediction of World Champion, than **NOB** has won. But this criterion is too coarse. A bit better might be the number of correct predictions of qualification (**CP**). In this case, the best prediction is done by **GOP,NOB** and **SUD**. But keep in mind, a single match that goes differently by a single penalty, like Spain against Russia can turn the whole ranking. Therefore, also the number of **correct predictions** is not suitable, it just a sidemark. If we use the prediction score every prediction takes into account. But even in this case, the decision might not be as clear as one might think. The group stage is significantly different from the knockout stage.
-To give a rough overview about the significance of the result we have assumed that for every single prediction the statistical error is 1% (rough estimate). With usual error propagation one can deduce an error estimation for $P$. This error is shown in the above chart by grey error bars. As can be seen, the first three predictions are within this error bars equal.
+To give a rough overview about the significance of the result let us assume, that for every single prediction the statistical error is 1% (rough estimate). With usual error propagation one can deduce an error estimation for $P$. This error is shown in the above chart by grey error bars. As can be seen, the first three predictions are within this error bars equal and fourth and fifth place are not that far away.
-Anyway, let us draw a conclusion and keep in mind the above reasoning. The //best// prediction was done by **FTE**, and with a small gap **GOP** and **SUD** are //second best//.
+Anyway, let us draw a conclusion and keep in mind the above reasoning. The //best// prediction was done by **FTE**, and with a small gap **GOP** and **SUD** are the //second best//.