One way to design a spam filter is to look at the words in an email. In particular, some words are more frequent in spam emails. Suppose that we have the following information: 50% of emails are spam; 1% of spam emails contain the word "refinance"; 001% of non-spam emails contain the word "refinance". Suppose that an email is checked and found to contain the word "refinance". What is the probability that the email is spam?

0.99

Step-by-step explanation:

Using Bayes theorem, let A be the event that the email is spam and B is the event that the email contains the word refinance.

A|B is the event that the email is a spam knowing that it contains the word "refinance". We are looking for the probability of this P(A|B)

B|A is the event that the email contains the word "refinance" given that it's a spam. P(B|A) = 0.01

P(A) is the probability that the email is spam = 0.5

P(B) is the probability that the email contains the word "refinance" = 0.5*0.01 + 0.5*0.0001 = 0.00505

Bayes formula

So the probability that the email is a spam is roughly 0.99

answer: are you

step-by-step explanation:

hope it

step-by-step explanation:

x^(1/6) · x^(1/6) · x^(1/6)   ·x^(1/6) = x^(4/6)   since we add the exponents

4/6 can be simplified to 2/3

the simplified form is x^(2/3)