Conditional normal distribution

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The discussion revolves around calculating the probability that random variable A, distributed as N(129, 29.4), is at least twice the size of random variable B, distributed as N(86, 24.0). Participants express uncertainty about using the Central Limit Theorem (CLT) in a conditional context and seek clarification on notation, specifically whether 'b' refers to variance or standard deviation. It is confirmed that 'b' represents the standard deviation and that A and B are independent variables. The conversation highlights the need for clear definitions and understanding of the relationship between the two variables to solve the problem effectively.
Gauss M.D.
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Homework Statement



We have two normally distributed random variables:

A = N(129, 29.4)
B = N(86, 24.0)

What is the probability A is atleast twice the size of B?

The Attempt at a Solution



P(A > 2B | B = b) or something? I think we are supposed to use the CLT somehow but I don't know how when it's conditional...
 
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Gauss M.D. said:

Homework Statement



We have two normally distributed random variables:

A = N(129, 29.4)
B = N(86, 24.0)

What is the probability A is atleast twice the size of B?

The Attempt at a Solution



P(A > 2B | B = b) or something? I think we are supposed to use the CLT somehow but I don't know how when it's conditional...

In the notation N(a,b), is b the variance or the standard deviation? I have seen both conventions used, so you need to tell us which one you mean. Also: are A and B independent?---you need to tell us that, too.
 
b is the stdev. A and B are independent. Sorry!
 
Question: A clock's minute hand has length 4 and its hour hand has length 3. What is the distance between the tips at the moment when it is increasing most rapidly?(Putnam Exam Question) Answer: Making assumption that both the hands moves at constant angular velocities, the answer is ## \sqrt{7} .## But don't you think this assumption is somewhat doubtful and wrong?

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