The statement "B is 7, P is 6, B is 5" appears to present conflicting information about the values assigned to B. If B is 7 in the first instance but is also stated to be 5 later, this inconsistency suggests that the context or conditions under which B is defined may have changed. Meanwhile, P remains consistently defined as 6. Clarifying the context or the rules governing these values would be necessary to resolve the contradiction.
probability of a machine component failing = 2/7 P(at least 4 failed) = P( 4 failed)+P(5 failed) +P(6 failed)+P(7 failed) Using binomial probability: P(4 failed ) =7C4 (2/7)^4 ((5/7)^3 = 0.084987 P(5 failed) = 7C5 (2/7)^5 (5/7)^2 = 0.020395 P(6 failed ) = 7C6 (2/7)^6 (5/7) = 0.002719 P(7 failed) = (2/7)^7 = 0.000155 Adding, P(at least 4 failures) = 0.108257
First, note that one even is independent of the other. If A and B are two independent events, the probability of A and B, written P(A and B) is P(A)xP(B). So if event A is the probability of a 5, P(A)=1/6 and if B is heads, P(B)=1/2 So P(A and B)=1/6 x1/2=1/12
==>-3p+7=5-8p+6 ==>5p+7=11 ==>5p=4 ==>p=4/5
There are symbols missing from your question which I cam struggling to guess and re-insert. p(a) = 2/3 p(b ??? a) = 1/2 p(a ∪ b) = 4/5 p(b) = ? Why use the set notation of Union on the third given probability whereas the second probability has something missing but the "sets" are in the other order, and the order wouldn't matter in sets. There are two possibilities: 1) The second probability is: p(b ∩ a) = p(a ∩ b) = 1/2 → p(a) + p(b) = p(a ∪ b) + p(a ∩ b) → p(b) = p(a ∪ b) + p(a ∩ b) - p(a) = 4/5 + 1/2 - 2/3 = 24/30 + 15/30 - 20/30 = 19/30 2) The second and third probabilities are probabilities of "given that", ie: p(b|a) = 1/2 p(a|b) = 4/5 → Use Bayes theorem: p(b)p(a|b) = p(a)p(b|a) → p(b) = (p(a)p(b|a))/p(a|b) = (2/3 × 1/2) / (4/5) = 2/3 × 1/2 × 5/4 = 5/12
p + 7 = 13 p = 6
how to solve 7 + p = p +7
Think Snooker: Black is 7, Pink is 6, Blue is 5. And there's ya answer. From Nightfire-Player. (no account here yet)
Consider the three events: A = rolling 5, 6, 8 or 9. B = rolling 7 C = rolling any other number. Let P be the probability of these events in one roll of a pair of dice. Then P(A) = P(5) + P(6) + P(8) + P(9) = 18/36 = 1/2 P(B) = P(7) = 6/36 = 1/6 and P(C) = 1 - [P(A) + P(B)] = 1/3 Now P(A before B) = P(A or C followed by A before B) = P(A) + P(C)*P(A before B) = 1/2 + 1/3*P(A before B) That is, P(A before B) = 1/2 + 1/3*P(A before B) or 2/3*P(A before B) = 1/2 so that P(A before B) = 1/2*3/2 = 3/4
What is the correct answer?
dependent because your changing
probability of a machine component failing = 2/7 P(at least 4 failed) = P( 4 failed)+P(5 failed) +P(6 failed)+P(7 failed) Using binomial probability: P(4 failed ) =7C4 (2/7)^4 ((5/7)^3 = 0.084987 P(5 failed) = 7C5 (2/7)^5 (5/7)^2 = 0.020395 P(6 failed ) = 7C6 (2/7)^6 (5/7) = 0.002719 P(7 failed) = (2/7)^7 = 0.000155 Adding, P(at least 4 failures) = 0.108257
First, note that one even is independent of the other. If A and B are two independent events, the probability of A and B, written P(A and B) is P(A)xP(B). So if event A is the probability of a 5, P(A)=1/6 and if B is heads, P(B)=1/2 So P(A and B)=1/6 x1/2=1/12
P = 5 A = 6 B = 11 Or.... P = 1 A = 30 B = 55
==>-3p+7=5-8p+6 ==>5p+7=11 ==>5p=4 ==>p=4/5
6*abs(b - p) which can also be written as 6*|b - p|
A prime triplet contains a pair of twin primes (p and p + 2, or p + 4 and p+ 6), a pair of cousin primes (pand p + 4, or p + 2 and p + 6), and a pair of sexy primes (p and p + 6).
There are symbols missing from your question which I cam struggling to guess and re-insert. p(a) = 2/3 p(b ??? a) = 1/2 p(a ∪ b) = 4/5 p(b) = ? Why use the set notation of Union on the third given probability whereas the second probability has something missing but the "sets" are in the other order, and the order wouldn't matter in sets. There are two possibilities: 1) The second probability is: p(b ∩ a) = p(a ∩ b) = 1/2 → p(a) + p(b) = p(a ∪ b) + p(a ∩ b) → p(b) = p(a ∪ b) + p(a ∩ b) - p(a) = 4/5 + 1/2 - 2/3 = 24/30 + 15/30 - 20/30 = 19/30 2) The second and third probabilities are probabilities of "given that", ie: p(b|a) = 1/2 p(a|b) = 4/5 → Use Bayes theorem: p(b)p(a|b) = p(a)p(b|a) → p(b) = (p(a)p(b|a))/p(a|b) = (2/3 × 1/2) / (4/5) = 2/3 × 1/2 × 5/4 = 5/12