Consider babies born in the "normal" range of \(37-43\) weeks gestational age.
The paper referenced in Example \(7.27\) ("Fetal Growth Parameters and Birth
Weight. Their Relationship to Neonatal Body Composition." Ultrasound in
Obstetrics and Gynecology [2009]: \(441-446\) ) suggests that a normal
distribution with mean \(\mu=3500\) grams and standard deviation \(\sigma=\) 600
grams is a reasonable model for the probability distribution of the continuous
numerical variable \(x=\) birth weight of a randomly selected full-term baby.
a. What is the probability that the birth weight of a randomly selected full-
term baby exceeds \(4000 \mathrm{~g}\) ? is between 3000 and \(4000 \mathrm{~g}
?\)
b. What is the probability that the birth weight of a randomly selected full-
term baby is cither less than \(2000 \mathrm{~g}\) or greater than \(5000
\mathrm{~g}\) ?
c. What is the probability that the birth weight of a randomly selected full-
term baby exceeds 7 pounds? (Hint: \(1 \mathrm{lb}=453.59 \mathrm{~g} .\) )
d. How would you characterize the most extreme \(0.1 \%\) of all full-term baby
birth weights?
e. If \(x\) is a random variable with a normal distribution and \(a\) is a
numerical constant \((a \neq 0)\), then \(y=a x\) also has a normal distribution.
Use this formula to determine the distribution of full-term baby birth weight
expressed in pounds (shape, mean, and standard deviation), and then
recalculate the probability from Part (c). How does this compare to your
previous answer?