Question

In: Statistics and Probability

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

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

Solutions

Expert Solution

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


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