Assume that the mean weight of 1-year-old girls in the US is normally distributed with a mean of about 9.5 grams with a standard deviation of approximately 1.1 grams. Without using a calculator estimate the percentage of 1-year-old girls in the US that meet the following conditions. Draw a sketch and shade the proper region for each problem. Less than 8.4 kg Between 7.3 kg and 11.7 kg More than 12.8 kg
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 that the mean weight of 1-year-old girls in the US is
mean of about 9.5 grams with a standard deviation of approximately 1.1 grams. Without
using a calculator estimate the percentage of 1-year-old girls in the US that meet the
following conditions. Draw a sketch and shade the proper region for each problem.
Less than 8.4 kg
Between 7.3 kg and 11.7 kg
More than 12.8 kg
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