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"In fact, whenever people make decisions after being supplied with the standard deviation number, they act as if it were the expected mean deviation." Boy, is that statement useless without any kind of context, example or citation.
The next two paragraphs have examples with some context.
"In fact, whenever people make decisions after being supplied with the standard deviation number, they act as if it were the expected mean deviation." Boy, is that statement useless without any kind of context, example or citation.
- Claims it is useless therewithout.
While the mean deviation as presented is slightly nicer than sigma for intuitive purposes, it isn't as appropriate (iirc) for statistical tests on normal distributions and t-distributions. More importantly, it doesn't fix the real problem, which is that the mean and standard deviation don't tell you everything you need to know about a data set, but often people like to pretend they do. It's not rare to read a paper i…
Without computers, this would be a waste of paper, but transmitting the data electronically is cheap.
So why argue over the measurements? Publish the data and my software can give me any measurement I'm interested in.
I think it's rather silly to talk about "retiring" standard deviation, but we can't blame Taleb - the publication itself posed the question "2014: What Scientific Idea is Ready for Retirement?" to various scientific personalities.
What Taleb failed to mention is that, once properly understood, standard deviation has distribution interpretations that can be much more useful than MAD. For example, if the data is approximately normally distributed, then there is approximately a 99.99% probability that the next data observation will be Not everything is approximately normally distributed, but a lot of phenomena ARE normally distributed. It's a well known fact that the phenomena which Taleb is most interested in (namely, financial return time-series) are not normally distributed. But I would like to know how Taleb proposes to "retire" volatility (sigma) from financial theory and replace it with MAD? Standard deviation is so central in finance that even the prices of some financial instruments (options) are quoted in terms of standard deviation (e.g. "That put option is currently selling at 30% vol"). How do we rewrite Black-Scholes option pricing theory and Markowitz portfolio theory in terms of MAD and remove all the sigmas everywhere? Surely Taleb has already written that paper for us so that we can retire standard deviation?
>>The notion of standard deviation has confused hordes of scientists
What an assertion! It also proved to be very useful for hordes of scientists... what about some examples of confused scientists ?
>>There is no scientific reason to use it in statistical investigations in the age of the computer
As someone who uses it daily I am eagerly awaiting his argument.
>>Say someone just asked you to measure the "average daily variations" for the temperature of your town (or for the stock price of a company, or the blood pressure of your uncle) over the past five days. The five changes are: (-23, 7, -3, 20, -1). How do you do it?
Ok... if I am to calculate the average I am calculating the average if I need to know standard deviation I calculate standard deviation...
>> It corresponds to "real life" much better than the first—and to reality.
What the flying fuck. What "real life" ? Standard deviation tells you how volatile measurements are not what mean deviation is. Those are both very real life things just not the same thing.
>>It is all due to a historical accident: in 1893, the great Karl Pearson introduced the term "standard deviation" for what had been known as "root mean square error". The confusion started then: people thought it meant mean deviation.
I don't know how one can read it and not think: "is this guy high or just stupid?".
>>. The confusion started then: people thought it meant mean deviation.
I am yet to see anybody who thinks that standard deviation is mean deviation. It's Taleb though. Baseless assertions insulting groups of people are his craft.
>>What is worse, Goldstein and I found that a high number of data scientists (many with PhDs) also get confused in real life.
One example please ? I can give hundreds when std dev is useful and mean deviation isn't. Anything when you decide what % of yoru bankroll to bet on perceived edge for example.
Ok so he asserted that people should just use mean deviation instead of mean of squares. Guess what though, taking the squares have a purpose: it penalizes big deviations so two situations which have the same mean deviation but one is more stable have different standard deviations. THis information is useful for many things: risk estimation or calculating sample size needed for required confidence (if you need more experiments, how careful should you be with conclusions and predictions etc). He didn't mention how are we going to achieve those with his proposal. Meanwhile he managed to throw insults towards various groups without giving one single example of misuse he describes.
This is not the first time he writes something this way. His whole recent book is like that. It's anti-intellectual bullshit with many words and zero points. He doesn't give any arguments, he throws a lot of insults, he misues words and makes up redundant terms which he then struggles to define. The guy is a vile idiot of the worst kind: ignorant and aggressive. Him gaining so much following by spewing nonsense like this article is for sure fascinating but there is no place for him in any serious debate.
State the sample size and standard deviation?
Squaring error isn't just a convenient way to remove sign, it's driven by a lot of data-sets' conformance to the central limit theorem.
"In fact, whenever people make decisions after being supplied with the standard deviation number, they act as if it were the expected mean deviation." Boy, is that statement useless without any kind of context, example or citation.
- Strips a statement of context, examples, and citations. - Claims it is useless therewithout.