Question

What level of alpha and beta errors are you willing to accept for medical testing? Why? What level would you set for alpha? Why?

Answer 1

Type I error(alpha error)

When the null hypothesis is true and you reject it, you make a type I error. The probability of making a type I error is α, which is the level of significance you set for your hypothesis test. So rejecting null when it is true is type I error...

Type II error(beta error)

When the null hypothesis is false and you fail to reject it, you make a type II error. The probability of making a type II error is β, which depends on the power of the test. You can decrease your risk of committing a type II error by ensuring your test has enough power...so beta error is accepting null when it is false..

An α of 0.05 indicates that you are willing to accept a 5% chance that you are wrong when you reject the null hypothesis. To lower this risk, you must use a lower value for α. However, using a lower value for alpha means that you will be less likely to detect a true difference if one really exists....so for alpha we should set the as low as possible to make the error minimum......hence we should choose alpha like .05,.01 ,.005 etc....

Note-if there is any understanding problem regarding this please feel free to ask via comment box..thank you