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scoundrel [369]
3 years ago
9

Please help ! Please help!

Mathematics
1 answer:
son4ous [18]3 years ago
6 0

Answer:

x=139 i believe not 100% about it though its been years since ive done this work.

Step-by-step explanation:

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Bayes' rule can be used to identify and filter spam emails and text messages. This question refers to a large collection of real
Blababa [14]

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0.134 = 13.4% probability that a message is spam, given that it contains the word "text" (or "txt")

Step-by-step explanation:

We use the conditional probability formula to solve this question. It is

P(B|A) = \frac{P(A \cap B)}{P(A)}

In which

P(B|A) is the probability of event B happening, given that A happened.

P(A \cap B) is the probability of both A and B happening.

P(A) is the probability of A happening.

In this question:

Event A: Contains the word "text", or "txt".

Event B: Spam message.

The word "text" (or "txt") is contained in of all messages, and in of all spam messages.

This means that P(A) = 1

747 of the 5574 total messages () are identified as spam. The word "text" (or "txt") is contained in all of them. So

P(A \cap B) = \frac{747}{5574} = 0.134

Then

P(B|A) = \frac{P(A \cap B)}{P(A)} = \frac{0.134}{1} = 0.134

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4 years ago
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