Question 1163212
<font face="Times New Roman" size="+2">


A type I error is a rejection of a null hypothesis when the null hypothesis is indeed true.


A type II error is an acceptance of a null hypothesis when the null hypothesis is indeed false.


So, what is the probability that the blood test says the person has the disease (null hypothesis rejected) when in fact the person does not (null hypothesis true)?


And what is the probability that the blood test says the person does not have the disease (null hypothesis accepted) when the person does in fact have the disease (null hypothesis false)?
								
								
John
*[tex \LARGE e^{i\pi}\ +\ 1\ =\ 0]
My calculator said it, I believe it, that settles it
<img src="http://c0rk.blogs.com/gr0undzer0/darwin-fish.jpg">
*[tex \Large \ \
*[tex \LARGE \ \ \ \ \ \ \ \ \ \  
								
{{n}\choose{r}}
</font>