Probability Theory: Solutions to Exam 1, Spring 2007, Exams of Engineering

The solutions to exam 1 of the probability theory course offered in spring 2007. It includes calculations for various probabilities using bayes' theorem and conditional probabilities. Students can use this document to check their understanding of the concepts covered in the exam.

Typology: Exams

Pre 2010

Uploaded on 03/10/2009

koofers-user-i5t
koofers-user-i5t 🇺🇸

5

(1)

10 documents

1 / 3

Toggle sidebar

This page cannot be seen from the preview

Don't miss anything!

bg1
ESI 6321 Spring 2007
Exam 1 solutions
Problem 1
a) Denote by A,B,C,D, and Erespectively, the following events:
A: heart failure is due to induced substances
B: heart failure is due to outside factors
C: heart failure is due to natural occurrences
D: heart failure is due to disease
E: heart failure is due to infection
P(A) = P(A|B)·P(B) + P(A|C)·P(C)
= 0.73 ·0.13 + 0 ·0.87
= 0.0949
b) P(DE) = P(D) + P(E). Now,
P(D) = P(D|B)·P(B) + P(D|C)·P(C)
= 0 ·0.13 + 0.27 ·0.87
= 0.2349,
and
P(E) = P(E|B)·P(B) + P(E|C)·P(C)
= 0 ·0.13 + 0.17 ·0.87
= 0.1479.
Thus P(DE) = 0.2349 + 0.1479 = 0.3828.
Problem 2
a)
P(B|A) = 22
30
P(B) = 77
100
P(B|A)6=P(B)events A and B are not independent
1
pf3

Partial preview of the text

Download Probability Theory: Solutions to Exam 1, Spring 2007 and more Exams Engineering in PDF only on Docsity!

ESI 6321 – Spring 2007

Exam 1 solutions

Problem 1

a) Denote by A, B, C, D, and E respectively, the following events:

A : heart failure is due to induced substances B : heart failure is due to outside factors C : heart failure is due to natural occurrences D : heart failure is due to disease E : heart failure is due to infection

P (A) = P (A | B) · P (B) + P (A | C) · P (C) = 0. 73 · 0 .13 + 0 · 0. 87 = 0. 0949

b) P (D ∪ E) = P (D) + P (E). Now,

P (D) = P (D | B) · P (B) + P (D | C) · P (C) = 0 · 0 .13 + 0. 27 · 0. 87 = 0. 2349 , and

P (E) = P (E | B) · P (B) + P (E | C) · P (C)

Thus P (D ∪ E) = 0.2349 + 0.1479 = 0. 3828.

Problem 2

a)

P (B | A) =

P (B) =

P (B | A) 6 = P (B) ⇒ events A and B are not independent

b)

P (B | A) = 2230 = 1130 = 0. 733

Problem 3

Let A, B, C be the following events:

A = user is legitimate B = user is fraudulent C = call is originated from two or more metropolitan areas

From the problem statement we have:

P (C | B) = 0. 3 P (C | A) = 0. 01 P (B) = 0. 0001

Through Bayes’ theorem, we can now compute the required probability:

P (B | C) =

P (C | B) · P (B)

P (C | B) · P (B) + P (C | A) · P (A)

P (C | B) · P (B)

P (C | B) · P (B) + P (C | A) · (1 − P (B))

Problem 4

Define PA, PB , PC to be the probabilities that respectively A, B, and C function properly.

(a) PA = P (all 20 ICs of A work) = (1 − 0 .01)^20 = 0.8179.

(b) PB = 1 − P (none of the 20 ICs of B works) = 1 − 0. 0120 = 1 − 10 −^40.

(c) PC = P (20 ICs of C work) + P (19 ICs of C work) = (1 − 0 .01)^20 + C 1920 · (1 − 0 .01)^19 · 0. 011 =

  1. 98

(d) Let PD = P(product functions properly). Then PD = PA · PB · PC =. 80.

(e) Apply Bayes rule.

P (set A fails|product fails) = P (product fails|set A fails) × P (set A fails) P (product fails)

1 × (1 − PA)

1 − PD