{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

IndependenceConditioning

# IndependenceConditioning - Le arning Obje s ctive fine De...

This preview shows pages 1–9. Sign up to view the full content.

Learning Objectives Define conditional probability Calculate conditional probabilities for discrete events (e.g., coin tosses). Define independence

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Example Suppose that two doctors test all patients coming into a blood donation center for anemia. Suppose that the first doctor diagnoses 10% of all patients as positive, the second doctor diagnoses 17% of all the patients as positive, and both doctors diagnose 8% of all patients as positive. What is the conditional probability that the second doctor makes a positive diagnosis of anemia given that the first doctor makes a negative diagnosis?
Conditional Probability Reason based on partial information Conditional probability of A given B P ( A | B )

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Example Roll a fair six-sided di P( outcome is 6 ) = 1/6
Example Roll a fair six-sided di What is P(outcomeis 6| outcomeis even)? P( | ) = outcome is even outcome is 6 1/3

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Conditional Probability Conditional probability of A given B P ( A | B ) = P ( A B ) P ( B ) P ( A | B ) = P ( A B ) P ( B ) = 1 6 3 6 = 1 3
Example Roll two fair 6-sided dice A = both show the same number P( A ) = 6 / 36

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Example Roll two fair 6-sided dice B = their sum is not greater than 3 P( B ) = 3 / 36
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}