Software filters rely heavily on "blacklists" (lists of known "phishing" URLS) to detect fraudulent e-mails. But such filters typically catch only 21 percent of phishing URLS. Jason receives 18 phishing e-mails. (e) What is the expected number that would be caught by such a filter? (Round your answer to 2 decimal places.) Expected number (b) What is the chance that such a filter would detect none of them? (Round your answer to 5 decimal places.) Probability

A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
Publisher:Sheldon Ross
Chapter1: Combinatorial Analysis
Section: Chapter Questions
Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...
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Software filters rely heavily on "blacklists" (lists of known "phishing" URLs) to detect fraudulent e-mails. But such filters typically catch only 21 percent of phishing URLs. Jason receives 18 phishing e-mails. 

(a) What is the expected number that would be caught by such a filter? (Round your answer to 2 decimal places.)

| Expected number | _______________ | 

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

| Probability | _______________ |
Transcribed Image Text:Software filters rely heavily on "blacklists" (lists of known "phishing" URLs) to detect fraudulent e-mails. But such filters typically catch only 21 percent of phishing URLs. Jason receives 18 phishing e-mails. (a) What is the expected number that would be caught by such a filter? (Round your answer to 2 decimal places.) | Expected number | _______________ | (b) What is the chance that such a filter would detect none of them? (Round your answer to 5 decimal places.) | Probability | _______________ |
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