Respuesta :
Answer and Explanation:
(a) Null hypothesis H0 : the new drug is safe.
Alternative hypothesis H1 : the drug is not safe.
(b) Type I error: Rejecting H0 when it is true. So, the drug is not taken when the drug is safe.
Type II error: Accepting H0 when it is not true. So, the drug is taken when the drug is not safe.
(c) Type II error is more harmful than type I error. So, the probability P(TypeII error) = \beta should be minimized to increase the power of the test 1-\beta.
Answer:
a) safe, alternative hypothesis is that drug is unsafe
b) Type I: Drug is unsafe
Type II: Drug is safe
c) yes
Step-by-step explanation:
a) Null Hypothesis: Hypothesis stating that the claim is true and any difference in the result is only due to experimental error.
Alternate hypothesis: rejecting the claim.
b) type I error is incorrectly rejecting null hypothesis when it is actually true
type ii error is failure to reject null hypothesis when it is actually false
c) β is probability of type ii error
α is probabiltiy of type i error.
Both of these must be small for hypothesis testing