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That is absolute nonsense.

There is clear correlation between gender and survival rates. Given the data, a decent prior would absolutely take that into account.

Yes, there are other factors. But the foundation of statistical models is simplification, and descriptive statistics are an important foundation of that.

In any case, it isn't exactly clear that there are magical hidden factors which predicted survival. It appears you maybe unfamiliar with the event, because basically those who got into a lifeboat survived, and those who didn't, didn't survive.

To quote Wikipedia:

Almost all those who jumped or fell into the water drowned within minutes due to the effects of hypothermia.... The disaster caused widespread outrage over the lack of lifeboats, lax regulations, and the unequal treatment of the three passenger classes during the evacuation..... The thoroughness of the muster was heavily dependent on the class of the passengers; the first-class stewards were in charge of only a few cabins, while those responsible for the second- and third-class passengers had to manage large numbers of people. The first-class stewards provided hands-on assistance, helping their charges to get dressed and bringing them out onto the deck. With far more people to deal with, the second- and third-class stewards mostly confined their efforts to throwing open doors and telling passengers to put on lifebelts and come up top. In third class, passengers were largely left to their own devices after being informed of the need to come on deck.

Even more tellingly:

The two officers interpreted the "women and children" evacuation order differently; Murdoch took it to mean women and children first, while Lightoller took it to mean women and children only. Lightoller lowered lifeboats with empty seats if there were no women and children waiting to board, while Murdoch allowed a limited number of men to board if all the nearby women and children had embarked

All this behavior matches exactly what the model tells us about the event.

I'd be very interested if you can point to something specific that is wrong about it.

All models are wrong, but some are useful.




I think you are making the point for him. If you look at the predictive models people make on these, they make a big deal about your sex and status being the main indicators of who survived. The reality is that the main causal indicator for survival was access to a lifeboat.

Now, it so happens that that correlated heavily with class. But, not as much as with sex. Though, there were some places where being male hurt your chances (as you point out in the one officer not allowing men on boats), by and large these were secondary and correlated with success, not predictors of it.


> All models are wrong, but some are useful.

Exactly.

All predictions are wrong and make no sense for partially observable, multiple causation, mostly stochastic phenomena. It will never be the same.


Except that this model was useful.

The Titanic's sister ship (the Brittanic) was torpedoed during WW1 and sunk. However, the lesson of the Titanic (too few lifeboats) had been learnt, and only 26 people died.

I don't know what point you are trying to make - yes, I agree that history never repeats, but lessons can be learnt from it, and they can be quantified and they can be useful.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1291331/


>> The Titanic's sister ship (the Brittanic) was torpedoed during WW1 and sunk. However, the lesson of the Titanic (too few lifeboats) had been learnt, and only 26 people died.

This happened because they made a _statistical_ model of the Titanic disaster, and learned from it? Like, they actually crunched the numbers and plotted a few curves etc, and then said "aha, we need more boats"?

I kind of doubt it, and if it wasn't the case then you can't very well talk about a "model", in this context. It's more like they had a theory of what factor most heavily affected survival and acted on it. But I'd be really surprised to find statistics played any role in this.


This happened because they made a _statistical_ model of the Titanic disaster, and learned from it?

No - statistics as the discipline that we think of today wasn't really around until the work of Gosset[1] and Fisher[2] which was done a few years after this.

I'm sure you noted that I was very careful with what I claimed: "the lesson of the Titanic (too few lifeboats) had been learnt".

These days we'd quantify the lesson with statistics. Then, they didn't have that tool.

Instead, we have testimony[3] relaying the same story: Just one question. Have you any notion as to which class the majority of passengers in your boat belonged? - (A.) I think they belonged mostly to the third or second. I could not recognise them when I saw them in the first class, and I should have known them if there were any prominent people. (Q.) Most of them were in the boat when you came along? - (A.) No. (Q.) You put them in? - (A.) No. Mr. Ismay tried to walk round and get a lot of women to come to our boat. He took them across to the starboard side then - our boat was standing - I stood by my boat a good ten minutes or a quarter of an hour. (Q.) At that time did the women display a disinclination to enter the boat? - (A.) Yes."

So yes, I agree - it was a theory, which our modern modelling tools can show matched well with what the statistics showed happened.

My whole point is that this is very useful, unlike the OP who dismissed it as useless.

[1] https://en.wikipedia.org/wiki/William_Sealy_Gosset

[2] https://en.wikipedia.org/wiki/Ronald_Fisher

[3] http://www.titanicinquiry.org/BOTInq/BOTInq33Header.php


My point was in my first comment.

OK, tell me, please, what it is that you can predict? That some John Doe, having the first class ticket in a cabin next to the exit would survive the collision of the next Titanic with a new iceberg? That being a woman gives you better chances to secure a seat in a lifeboat? What is the meaning of the word "predict" here?


Yes.




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