moments

The parent here makes a good point, and your comment appears to represent a common misconception about neurotransmitters. Both dopamine and serotonin can do different things depending on the system and the receptors that are actively present. Serotonin, for example, is mostly in your gut, not cortex! From wikipedia:

"Approximately 90% of the human body's total serotonin is located in the enterochromaffin cells in the GI tract, where it is used to regulate intestinal movements."

Dopamine is more specific, playing an important role in the limbic system, but is not limited to it. Its functions are not completely understood, and again depend on the receptor.

Better to think of the function of neurotransmitters as dependent on both system AND receptor. The function of neurotransmitters, like dopamine, can be simplified, but others, like glutamate, are extremely complicated.

How did you pick the window size used in the analysis? Did you try different window sizes?

I have seen many time-series analyses posted here lately, and all seem to use arbitrary window sizes.

Edit: PS, thanks for posting this and being around for questions.

To Be Human: long and comprehensive (not actually written by him, but a collection of his works).

Flight of the Eagle: short and comprehensive.

Freedom from the Known: short and practical.

While I agree with the spirit of this, the conclusion is not necessarily correct. The mean can be highly informative, but should never be used alone.

Assume you know only the mean revenue and the maximum revenue (but forgot to measure variance). You could make an extreme scenario with the maximum possible variance to generate a "worst case" distribution. In this scenario, all customers either provide zero revenue or the maximum. This distribution has the maximum possible variance for a given mean and maximum.

Will you be profitable this year? Your chances will be better than the worst case scenario described above! If higher moments are known (variance, skew, etc.), more accurate bounds can be found.

In conclusion, the mean can be very useful, especially if higher moments are known.

Thank you, this looks interesting. Also, a guy named Kent has a book on this called: Psychedelic Information Theory. There is a web print of the book floating around.

I never realized that the median is an average... interesting. So any average can be dominated by extreme events, except the median average.

Then we are discussing averages, in general. So, the common misconception would be:

-Averages are dominated by the median, and deviation from the mean is symmetric.-

Thank you for the interesting link.

>statistics tells us that 50 of them will do better than the market averages (and 50 will do worse)

This is a common misunderstanding, but actually 50% will do better than the median not the average. Averages can be dominated by extreme events, so more than 50% can do better (or worse) depending on the skew.

The author follows this rule: only recommend a strategy that is currently used.

If the advice goes badly, the author also suffers. Such recommendations are more reliable than those from authors without 'skin in the game'.