ADM 2302 Lecture Notes - Lecture 19: Breast Cancer Screening, Bayes Estimator, Mammography

45 views3 pages

Document Summary

> the application of bayes rule to compute posterior probability becomes more complex with larger problems but can be simpli ed by using tables. This approach is more systematic than direct bayes rule. > physician needs to estimate the chances that a woman has breast cancer (bc) given that she has a positive radiologist report from a mammography (rm+). The basis for physician making the assessment is as follows: (a) the probability that a patient has asymptomatic breast cancer is 1%. (p(bc) = 0. 01. > according to bayes rule, the probability that this patient has breast cancer is about. > experimental studies found that 95 out of 100 physicians estimated the probability of breast cancer after a positive radiologist report from mammography to be around. > with the above formulation using the frequencies format, 46% of the physicians made correct estimation. e. g, margaret is considering investing her savings in the ottawa real estate market.

Get access

Grade+20% off
$8 USD/m$10 USD/m
Billed $96 USD annually
Grade+
Homework Help
Study Guides
Textbook Solutions
Class Notes
Textbook Notes
Booster Class
40 Verified Answers
Class+
$8 USD/m
Billed $96 USD annually
Class+
Homework Help
Study Guides
Textbook Solutions
Class Notes
Textbook Notes
Booster Class
30 Verified Answers