Number of Multiple The data on the right represent the number of live multiple-delivery births (three or more babies) in a particular year for women 15 to 54 years old. Use the data to complete parts (a) through (d) below. Births Age 15-19 95 20-24 508 25-29 1622 30-34 2835 35-39 1843 40-44 377 45-54 117 (a) Determine the probability that a randomly selected multiple birth for women 15-54 years old involved a mother 30 to 39 years old. P(30 to 39) = 0.632 (Type an integer or decimal rounded to three decimal places as needed.) (b) Determine the probability that a randomly selected multiple birth for women 15-54 years old involved a mother who was not 30 to 39 years old. P(not 30 to 39) = (Type an integer or decimal rounded to three 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!
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