Don't you think that applying mathematical models without understanding of all the causes and their relative weights would yield a meaningless results (not even approximate ones)?
There are innumerable cases of misapplication of statistics (without even having a third control group) and probability distributions to incomplete or simply irrelevant data in history of so called data-driven sciences?
Math is a tool, and application of it to a poorly understood context will lead to false conclusions or mistaking a correlation for causation. Correlations, by the way, could be found everywhere, especially when there is a prize hunt for them.
Back to the subject - tribal eating habits are driven by availability of food sources in a particular location, and the traditional dishes usually were evolved to give the best ratios possible. The case of Tibetan nutrition, which is based on barley flour and yak butter is the good example. Traditional Nepalese food, which varies according to altitude, is another one.
There are innumerable cases of misapplication of statistics (without even having a third control group) and probability distributions to incomplete or simply irrelevant data in history of so called data-driven sciences?
Math is a tool, and application of it to a poorly understood context will lead to false conclusions or mistaking a correlation for causation. Correlations, by the way, could be found everywhere, especially when there is a prize hunt for them.
Back to the subject - tribal eating habits are driven by availability of food sources in a particular location, and the traditional dishes usually were evolved to give the best ratios possible. The case of Tibetan nutrition, which is based on barley flour and yak butter is the good example. Traditional Nepalese food, which varies according to altitude, is another one.