Hi, I'm missing a bit of context to be able to answer your question with confidence. The concepts are not the same thing, but there are some similarities. For example: If you average n iid random variables, the standard deviation of this mean goes to zero as n goes to infinity (law of large numbers). This kind of result is an example of a concentration inequality. Hope this helps.
I guess not just standard deviations, but the idea of t / z scores and such. The probability of a random variable being above or below certain values. These concepts seem to be what concentration inequalities are getting at, unless I am completely misunderstanding what they are. It seems to be concentration inequality may be a general idea of this concept? Additionally you can calculate confidence intervals to determine the interval the true mean lies in with a certain confidence
concentration inequalities vs standard deviation
Hi, i was wondering how the idea of concentration inequalities and generalization error differs from the idea of standard deviation?
Hi, I'm missing a bit of context to be able to answer your question with confidence. The concepts are not the same thing, but there are some similarities. For example: If you average n iid random variables, the standard deviation of this mean goes to zero as n goes to infinity (law of large numbers). This kind of result is an example of a concentration inequality. Hope this helps.
I guess not just standard deviations, but the idea of t / z scores and such. The probability of a random variable being above or below certain values. These concepts seem to be what concentration inequalities are getting at, unless I am completely misunderstanding what they are. It seems to be concentration inequality may be a general idea of this concept? Additionally you can calculate confidence intervals to determine the interval the true mean lies in with a certain confidence
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