Why is statistical significance not necessarily of practical important difference to a business decision? ?
Why is statistical significance not necessarily of practical important difference to a business decision? ? Give an example and explain. Why do statisticians play only a limited role in deciding whether statistical significance requires a business action?
b. In a hypothesis for a proportion, when can normality be assumed? If the sample size is too small to assume normality, what can we do?
In your average business action, there tend to be too many variables. Statistical significance isn't going to play as large of a role if it can't actually say with relative certainty that all of the variables will lead to some event (i.e. it might be able to predict that based on variables x1, x2, x3, event E will happen, but once you throw in x4 ~ x25, it becomes more difficult). There are probably other, better reasons as well.
b) I think it's something like p*n >=10 or >=30, as well as (1-p)*n >=10 or >=30. (I think it's 10, but I seem to remember 30 from something).
So if p = 0.01, n should be > 1000 or 3000 or something.
If it's not normal, you can simply use a non-normal distribution (T, for instance) instead of a normal distribution.
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