And BTW they just excluded Katrina as an outlier. While not necessarily a totally unwarranted decision, it makes already marginal conclusions that much more so.
Isn't this conclusion more significant because Katrina is excluded?
Edit: I meant the layman's sense of "significant" here. I just don't see how excluding Katrina "makes already marginal conclusions that much more so". I read your "but" statement as just saying that they haven't necessarily proven causality, but I don't see what that has to do with my statement.
Well, the word "significant" is a loaded one in this discussion -- in this context, it typically means "statistically significant," which has a very narrow (and sometimes questionable[1]) meaning.
You're right that leaving Katrina in the dataset (assuming the same techniques were used -- there are other ways to deal with outliers other than dropping them) would bias the result further towards indicating that female-named hurricanes are more dangerous. But the persistence of a significant finding in that regard in the absence of that data point does not prove a causal link, much less the specific one the author suggests.
It was intended more as a general point about picking and choosing of data. You're of course correct that including Katrina would buttress the female hurricane deadliness theory but would also open up the study to charges that it was influenced by a single outlier.
Edit: I meant the layman's sense of "significant" here. I just don't see how excluding Katrina "makes already marginal conclusions that much more so". I read your "but" statement as just saying that they haven't necessarily proven causality, but I don't see what that has to do with my statement.