Answer:
21
Step-by-step explanation:
Answer:
![= { \tt{ \frac{2}{5} \div \frac{3}{7} }} \\ \\ = { \tt{ \frac{2}{5} \times \frac{7}{3} }} \\ \\ = { \underline{ \tt{ \: \: \frac{14}{15} \: \: }}}](https://tex.z-dn.net/?f=%20%3D%20%7B%20%5Ctt%7B%20%5Cfrac%7B2%7D%7B5%7D%20%20%5Cdiv%20%20%5Cfrac%7B3%7D%7B7%7D%20%7D%7D%20%5C%5C%20%20%5C%5C%20%20%3D%20%7B%20%5Ctt%7B%20%5Cfrac%7B2%7D%7B5%7D%20%5Ctimes%20%20%5Cfrac%7B7%7D%7B3%7D%20%20%7D%7D%20%5C%5C%20%20%5C%5C%20%20%3D%20%7B%20%5Cunderline%7B%20%5Ctt%7B%20%5C%3A%20%20%5C%3A%20%20%5Cfrac%7B14%7D%7B15%7D%20%20%5C%3A%20%20%5C%3A%20%7D%7D%7D)
<u>Answer</u><u>:</u><u> </u><u>B</u>
Answer:
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Step-by-step explanation:
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a. By definition of conditional probability,
P(C | D) = P(C and D) / P(D) ==> P(C and D) = 0.3
b. C and D are mutually exclusive if P(C and D) = 0, but this is clearly not the case, so no.
c. C and D are independent if P(C and D) = P(C) P(D). But P(C) P(D) = 0.2 ≠ 0.3, so no.
d. Using the inclusion/exclusion principle, we have
P(C or D) = P(C) + P(D) - P(C and D) ==> P(C or D) = 0.6
e. Using the definition of conditional probability again, we have
P(D | C) = P(C and D) / P(C) ==> P(D | C) = 0.75