Galton recorded the heights of 8585 men in Great Britain. This forms a normal distribution with mean 67 inches and a standard deviation of 2.5". L6'oでうと(h)How much would a baby have to weigh to be among the heaviest 10% of all newbornsStとレっ2u3954,85S Grams2.In the mid-19thcentury, Sir Francis Galton demonstrated, through extensive datacollection, that many human characteristics such as height and 1Q are distributedthroughout the entire population in accordance with the normal distribution. Galtonrecorded the heights of8585 men in Great Britain. This forms a normal distribution witmean 67µ=inches and standard deviation 2.5o=inches.(a)Graph this normal distribution and label the x-axis.(b)What proportion of these men were between 66 and 68 inches tall?

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MATLAB: An Introduction with Applications

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Galton recorded the heights of 8585 men in Great Britain. This forms a normal distribution with mean 67 inches and a standard deviation of 2.5".

L6'oでうと
(h)How much would a baby have to weigh to be among the heaviest 10% of all newborns
Stと
レっ2u
3954,85S Grams
2.In the mid-19thcentury, Sir Francis Galton demonstrated, through extensive data
collection, that many human characteristics such as height and 1Q are distributed
throughout the entire population in accordance with the normal distribution. Galton
recorded the heights of8585 men in Great Britain. This forms a normal distribution wit
mean 67µ=inches and standard deviation 2.5o=inches.
(a)Graph this normal distribution and label the x-axis.
(b)What proportion of these men were between 66 and 68 inches tall?

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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