Answer:
<h2>1</h2>
Step-by-step explanation:
I hope this helps
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
Answer:
25x + 55
Step-by-step explanation:
10(x + 4) + 15(x + 1)
Distribute
10x + 40 + 15x +15
Combine like terms
25x + 55
