Assume the birth weights at a local hospital have a normal distribution with a mean of 110 oz and a standard deviation of 15 oz. a. What is the percentile rank for a baby who is 140 oz. b. According to the Empirical Rule what percent of babies will be heavier than 155oz? c. According to the Empirical Rule what percent of babies would you expect to find between 80 oz and 125 oz?
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!
Assume the birth weights at a local hospital have a
a. What is the percentile rank for a baby who is 140 oz.
b. According to the
c. According to the Empirical Rule what percent of babies would you expect to find between 80 oz and 125 oz?
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