Question

Software filters rely heavily on “blacklists” (lists of known “phishing” URLs) to detect fraudulent e-mails. But such filters typically catch only 20 percent of phishing URLs. Jason receives 14 phishing e-mails.

(a)
What is the expected number that would be caught by such a filter? (Round your answer to the next whole number.)

Expected number

(b)
What is the chance that such a filter would detect none of them? (Round your answer to 5 decimal places.)

Probability

Answer 1

Answer on Question #40901 – Math -Complex Analysis

Question:

Software filters rely heavily on “blacklists” (lists of known “phishing” URLs) to detect fraudulent e-mails. But such filters typically catch only 20 percent of phishing URLs. Jason receives 14 phishing e-mails.

(a) What is the expected number that would be caught by such a filter? (Round your answer to the next whole number.)

Expected number

(b) What is the chance that such a filter would detect none of them? (Round your answer to 5 decimal places.)

Answer:

The probability that the one letter will be cathed is 0.2 and the probability that such a filter would not detect phishing letter is 0.8.

a) The expected number of letters that would be caught by such a filter is $14 \times 0.2 = 2.8 = 3$.

b) The chance that such a filter would detect none of 14 letter is $(0.8)^{14} = 0.04398$.