A random number generator picks a number from 15 to 60 in a uniform manner. Round answers to 4 decimal places when possible. The mean of this distribution is The standard deviation is The probability that the number will be exactly 57 is P(x = 57) = The probability that the number will be between 29 and 35 is P(29 < x < 35) = The probability that the number will be larger than 40 is P(x > 40) = P(x > 29 | x < 51) = Find the 80th percentile. Find the minimum for the upper quartile.
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
A random number generator picks a number from 15 to 60 in a uniform manner. Round answers to 4 decimal places when possible.
- The mean of this distribution is
- The standard deviation is
- The
probability that the number will be exactly 57 is P(x = 57) = - The probability that the number will be between 29 and 35 is P(29 < x < 35) =
- The probability that the number will be larger than 40 is P(x > 40) =
- P(x > 29 | x < 51) =
- Find the 80th percentile.
- Find the minimum for the upper
quartile .
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