In a survey of a group of men, the heights in the 20-29 age group were normally distributed, with a mean of 67.7 inches and a standard deviation of 3.0 inches. A study participant is randomly selected. Complete parts (a) through (d) below. c) Find the probability that a study participant has a height that is more than 71 inches. The probability that the study participant selected at random is more than 71 inches tall is nothing. (Round to four decimal places as needed.)
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!
In a survey of a group of
men, the heights in the 20-29 age group were
inches and a standard deviation of
inches. A study participant is randomly selected. Complete parts (a) through (d) below.
The Z-score of a random variable X is defined as follows:
Z = (X – µ)/σ.
Here, µ and σ are the mean and standard deviation of X, respectively.
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