Asked by J'Ona Wells on May 29, 2024
Verified
Think about a situation where you have a test for a virus.First,you are tested positive or negative.Second,you either really do have the virus or you don't.
a.If you actually have the virus but the test did not catch it,which error has been made and what is the impact of that error?
b.If you actually don't have the virus but the test says you did,which error is being made and what is the impact of this error?
c.Which error is the worst one to commit in this situation and why?
Type I Error
The mistake of rejecting a true null hypothesis or falsely claiming to detect an effect that does not actually exist.
Type II Error
A statistical mistake made by failing to reject a false null hypothesis; not detecting an effect or difference when there actually is one.
Test Impact
Measures the effect or change resulting from the introduction or implementation of a test or assessment.
- Acquire an understanding of the concepts related to Type I and Type II errors in the context of hypothesis evaluation.
- Examine the repercussions of committing Type I and Type II errors in practical scenarios.
Verified Answer
BT
Brandon TineoJun 01, 2024
Final Answer :
a. A Type II error has been committed,which is a very costly error.You are being told you are OK when you really have the virus,and you are going untreated.
b. This is a false alarm,and a Type I error.A Type I error causes undue worry on behalf of the person taking the test,and could cause some treatments to occur that shouldn't.
c. With a Type II error you are letting people with the virus go unnoticed,and hence untreated.With a Type I error you falsely tell them they have the virus.This can cause undue worry but it is certainly not as bad of a problem as letting someone go on not knowing they have the virus.A Type II error is the worst in this situation.
b. This is a false alarm,and a Type I error.A Type I error causes undue worry on behalf of the person taking the test,and could cause some treatments to occur that shouldn't.
c. With a Type II error you are letting people with the virus go unnoticed,and hence untreated.With a Type I error you falsely tell them they have the virus.This can cause undue worry but it is certainly not as bad of a problem as letting someone go on not knowing they have the virus.A Type II error is the worst in this situation.
Learning Objectives
- Acquire an understanding of the concepts related to Type I and Type II errors in the context of hypothesis evaluation.
- Examine the repercussions of committing Type I and Type II errors in practical scenarios.