DOC PREVIEW
H-SC MATH 121 - Lecture 3 Notes - Language of Decision Making 2

This preview shows page 1-2-3-4-5-6 out of 17 pages.

Save
View full document
View full document
Premium Document
Do you want full access? Go Premium and unlock all 17 pages.
Access to all documents
Download any document
Ad free experience
View full document
Premium Document
Do you want full access? Go Premium and unlock all 17 pages.
Access to all documents
Download any document
Ad free experience
View full document
Premium Document
Do you want full access? Go Premium and unlock all 17 pages.
Access to all documents
Download any document
Ad free experience
View full document
Premium Document
Do you want full access? Go Premium and unlock all 17 pages.
Access to all documents
Download any document
Ad free experience
View full document
Premium Document
Do you want full access? Go Premium and unlock all 17 pages.
Access to all documents
Download any document
Ad free experience
View full document
Premium Document
Do you want full access? Go Premium and unlock all 17 pages.
Access to all documents
Download any document
Ad free experience
Premium Document
Do you want full access? Go Premium and unlock all 17 pages.
Access to all documents
Download any document
Ad free experience

Unformatted text preview:

The Language of Statistical Decision MakingErrorsSlide 3Possible ErrorsDecisions and ErrorsSlide 6Slide 7ExampleSlide 9Safe and Effective CriteriaSignificance LevelSlide 12Slide 13Slide 14Two RollsSlide 16An Interesting StudyThe Language of Statistical Decision MakingLecture 3Section 1.3Mon, Jan 22, 2007ErrorsRecall our conclusion about the die being fair.Could our conclusion have been wrong?What would be the cause of our error?ErrorsHad we concluded that the die was not fair, could he have been wrong? What would be the cause of our error?Possible ErrorsWe might reject H0 when it is true.This is a Type I error.We might accept H0 when it is false.This is a Type II error.See Making Intelligent Errors, by Walter Williams.Decisions and ErrorsCorrectType IErrorCorrectType IIErrorState of NatureH0 true H0 falseAccept H0Reject H0DecisionDecisions and ErrorsCorrectType IErrorCorrectType IIErrorState of NatureH0 true H0 falseAccept H0Reject H0DecisionDecisions and ErrorsCorrectType IErrorCorrectType IIErrorState of NatureH0 true H0 falseAccept H0Reject H0DecisionExampleConsider a study to determine the effectiveness of a new drug.What are the two possible conclusions (hypotheses)?Which should get the benefit of the doubt?What are the two possible errors?Which is more serious?ExampleNow consider a study to determine the safety of a new drug.What are the two possible conclusions (hypotheses)?Which should get the benefit of the doubt?What are the two possible errors?Which is more serious?Safe and Effective CriteriaSafe and effectiveSignificance LevelSignificance Level – The likelihood of rejecting H0 when it is true, i.e., the likelihood of committing a Type I error. – The likelihood of a Type I error. – The likelihood of a Type II error.That is,  is the significance level.Significance LevelSuppose that we have two very unusual dice.Die A rolls a 1 80% of the time and a 6 only 20% of the time. (It never lands 2, 3, 4, or 5.)Die B rolls a 1 only 10% of the time and a 6 90% of the time. (It never lands 2, 3, 4, or 5.)Visually, the two dice are indistinguishable.Significance LevelWe are given one of the dice and we roll it one time.We get a 1.Suppose the null hypothesis is that we rolled die A and the alternative hypothesis is that we rolled die B.Which hypothesis do we choose?Significance LevelWhat is our criterion for choosing between the two hypotheses?Describe a Type I error.Describe a Type II error.What is the value of ?What is the value of ?Two RollsSuppose now that we roll the selected die twice and average the two rolls.We must get eitherA pair of 1s, with an average of 1.A 1 and a 6, with an average of 3.5.A pair of 6s, with an average of 6.Two RollsWhat would be a good criterion for decided which die it is?Based on this criterion,What is ?What is ?An Interesting StudyHair May Help Reveal Eating Disorders What were the hypotheses?Describe a Type I error.Describe a Type II


View Full Document

H-SC MATH 121 - Lecture 3 Notes - Language of Decision Making 2

Documents in this Course
Load more
Download Lecture 3 Notes - Language of Decision Making 2
Our administrator received your request to download this document. We will send you the file to your email shortly.
Loading Unlocking...
Login

Join to view Lecture 3 Notes - Language of Decision Making 2 and access 3M+ class-specific study document.

or
We will never post anything without your permission.
Don't have an account?
Sign Up

Join to view Lecture 3 Notes - Language of Decision Making 2 2 2 and access 3M+ class-specific study document.

or

By creating an account you agree to our Privacy Policy and Terms Of Use

Already a member?