Biostats help about power, confidence interval

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Jan 11, 2018
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I have a question from biostatistics regarding alpha error and beta error, power .

What I know:
alpha error is the chance that reject null when it is true. We want to minimize this kind of error so we arbitrarily keep alpha error as 5%

beta error is the chance of failing to reject null when null is false. Power(1 - beta error) is more important because the more the power, the greater the chance we reject null when it is actually false.

What my question is:
People assume alpha error % is same as p-value. How? And what is confidence interval in terms of this error?
1 - alpha error = confidence interval(95%) chance that that we accept null when its true.

Can anyone please take me on a journey of a basic study and its course? Study, standard errors, power, confidence interval.

Lets say we do a study a cohort study and identify the relative risk. Incidence among exposed/incidence among unexposed is 2.

How can we apply alpha error, beta error into such a study?

We find the confidence interval and see what the range of variability in the large population. We can find the confidence interval when we know the standard deviation. How do we get a standard deviation from our example study(above) when all it yields is the relative risk?

Thank you.

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Last edited:
for step know that increasing population size decreases confidence interval, increasing power as well. P value is the chance that an occurrence is due to pure chance and there is no correlation, meaning the chance that the results occurred just by coincidence, alpha is error in rejecting the null hypothesis, which is that there is no statistically sig difference, so both are separate concepts that lead to same conclusion, which is that there is nothing there.