Question

Name: Section Number To be graded assignments must be completed and submitted on the original book page Hypothesis Testing -As a Diagnostic Test ? Answer the following questions over the content material you just read or watched. 1. What is a false positive rate in the context of hypothesis testing? 2. What is the goal of hypothesis testing? 3. What is a Type I error, and how is it related to an "alpha level?" 4. What does it mean to say that the results of a hypothesis test are statistically significant? 5. What is a p-value, and what is the appropriate way to use one?

Answer 1

1) A false positive rate is the rate of falsely rejecting the Ho i.e. null hypothesis for a particular problem.

2) The goal of a hypothesis testing is to provide an evidence over the insignificance of of the alternate hypothesis i.e. the possibilty of not rejecting the null hypothesis.

3) A Type I error is defined as the possibility of rejecting Ho when Ho is true in nature i.e.
P(Type I error) = P(Rejecting Ho / Ho is true) <= $\alpha$   
i.e. the alpha level is the maximum value of P(Type I error).

4) When the results of a hypothesis test are statistically significant, then we conclude to reject the null hypothesis i.e. we accept the claim given in the alternative hypothesis.

5) In a hypothesis testing, a p-value is the probability of obtaining any possible extremes along with the assumption of the null hypothesis being true in nature. A p-value is used in making a decision about the rejection/ acceptance of a null hypothesis i.e. when the p-value < $\alpha$ , we reject the null hypothesis.

Hope this answers your query!