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Math Help - distribution

  1. #1
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    distribution

    Hiya!

    I need some help with these questions. I'm unsure where to start...

    1. Given that z is the standard normal random variable, find P(z > -1.62).

    2. Given a sample of ten numbers from 0 to 9 then the coefficient of variation for the same sample of 10 numbers is what?

    3. Y is a normally distributed random variable with mean 10 and standard deviation 4. Find the probabilty that Y is greater than 11.

    4. P(z >= c) = 0.8980, find c.

    5. Carpet manufacturer has a variety of carpet with an average of 1.5 flaws per square metre. These flaws are random and independent. Find the probabilty of fewer than two flaws in a random chosen square metre of carpet.

    Thanks!
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  2. #2
    Member Glaysher's Avatar
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    Quote Originally Posted by bennyya View Post
    Hiya!

    I need some help with these questions. I'm unsure where to start...

    1. Given that z is the standard normal random variable, find P(z > -1.62).

    2. Given a sample of ten numbers from 0 to 9 then the coefficient of variation for the same sample of 10 numbers is what?

    3. Y is a normally distributed random variable with mean 10 and standard deviation 4. Find the probabilty that Y is greater than 11.

    4. P(z >= c) = 0.8980, find c.

    5. Carpet manufacturer has a variety of carpet with an average of 1.5 flaws per square metre. These flaws are random and independent. Find the probabilty of fewer than two flaws in a random chosen square metre of carpet.

    Thanks!
    1. P(Z > -1.62) = P(Z < 1.62) by symmetry

    Look up 1.62 in your copy of the standard normal distrbution table

    2. Not sure what you mean

    3. Y~N(10, 4^2)

    P(Y > 11) = P(Z > (11 - 10)/4) = P(Z > 0.25) = 1 - P(Z < 0.25)

    Look up 0.25 in your table and stick it in the calculation

    4. P(Z > c) = 0.8980
    P(Z < -c) = 0.8980

    Look up the z value for 0.8980 in your table. Multiply it by -1 to find c

    5. X~Po(1.5)

    P(X < 2) = P(X = 0) + P(X = 1)

    Work out the probabilities individually and add them together using the formula for a Poisson distbution
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