on the limits of statistics | 16 comments (16 topical, editorial, 0 hidden)

Re: on the limits of statistics (none / 1)

I side with Taleb totally, in fact I gave the Black Swan to my PhD supervisor.

I have this plan to write a long article about uncertainty, error, belief revision especially in the context of what I perceive are natural Human biases (especially our psychological need of certainty - either offered by god, "science" or whatever).

Taleb is right, in my view, in that we create the illusion that we fully understand the past. Even for the past, there is incomplete information (I am not even talking about all the biases and propaganda on top of it).

If understanding the past is difficult (impossible), forecasting the future is an illusion. A necessary illusion (not only by psychological reasons, but also for pragmatical ones... we need to have some model of the future in order to plan ahead).

This is something not to be written in Internet Time(TM), but something I will be doing in the next months. So an answer to this (and other diaries in the same direction) will come, in the long, distant future... ;)

by t-------------- on Thu Sep 25th, 2008 at 06:53:03 PM EST

Re: on the limits of statistics (none / 0)

If understanding the past is difficult (impossible), forecasting the future is an illusion. A necessary illusion (not only by psychological reasons, but also for pragmatical ones... we need to have some model of the future in order to plan ahead).

There's no doubt that at a sufficiently philosophical level, any kind of forecast is an illusion. Hume rightly pointed out that we simply don't know if the sun is coming up tomorrow. Yet wheather forecasts, which are notoriously bad in the long term, are quite accurate in the very short term. It depends on the scope of the problem, and what the relevant constraints happen to be. It's quite accurate to predict a small dip in stock prices when dividends are being paid out, but forecasting economic indicators over years is highly tentative.

Some people would say that understanding (some aspect of) the past is an exercise in data compression: A good model is one which implies (generates) the past, but has a much simpler structure.

For example, flip a fair coin four or five times, and suppose that you observe the sequence HHHT. Even though the coin was fair, a simpler descriptive choice for this particular record of the past is to assume that the coin was biased in favour of H. Yet if you intend to forecast the next four flips, assuming a bias is not such a good idea.

--
$E(X_t|F_s) = X_s,\quad t > s$

by martingale on Thu Sep 25th, 2008 at 09:47:49 PM EST
[ Parent ]

Re: on the limits of statistics (none / 1)

Some people would say that understanding (some aspect of) the past is an exercise in data compression: A good model is one which implies (generates) the past, but has a much simpler structure.

While I understand that reasoning and partially agree with it, I would say that is worth pointing out that we are far from having complete information about the past (if that was such the case, courts would have 90% of the work done).

In fact you can create models of the past that are perfect at regenerating it and still be completely oblivious to the (hidden) fundamental variables. Actually, when you increase the complexity of a model, you have more chances of finding a "correct" recreation of the past as the model is able (just by the added complexity) to search a big chunk of the search space.

I have nothing against models (especially "rough" models are fundamental), I just think their use and the expectations on their ability to recreate the past/predict the future are highly overrated.

Believe it or not, I am currently doing sensitivity analysis to a model (studying the spread of malaria drug resistance considering different drug deployment policies).

by t-------------- on Fri Sep 26th, 2008 at 05:32:08 AM EST
[ Parent ]

Re: on the limits of statistics (none / 0)

Yes, I agree that complete information about the past is generally unattainable, and it's a right pain to deal with missing data. You have three years to figure out an answer, at least :)

--
$E(X_t|F_s) = X_s,\quad t > s$

by martingale on Fri Sep 26th, 2008 at 07:27:38 AM EST
[ Parent ]

on the limits of statistics | 16 comments (16 topical, 0 editorial, 0 hidden)

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