Compute each probability. The strategy is to transform X, a random variable representing the weight of newborns, to another random variable Z that represents the same but scaled quantity so that Z is normally distributed with mean 0 and s.d. 1. To do this, we use the rule
X = 5.5 + 1.6 Z
or
Z = (X - 5.5)/1.6
then use a calculator to compute the probability, or look it up in a table. Multiply this probability by 800 to find the number of newborns in each category.
1.
Pr[3 ≤ X ≤ 8] = Pr[(3 - 5.5)/1.6 ≤ (X - 5.5)/1.6 ≤ (8 - 5.5)/1.6]
… ≈ Pr[-1.5625 ≤ Z ≤ 1.5625]
… ≈ 0.8818
Out of 800 babies, you would expect around 88% of them, or about 705 babies to weight between 3 and 8 pounds.
2.
Pr[X < 6] = Pr[(X - 5.5)/1.6 ≤ (6 - 5.5)/1.6]
… = Pr[Z ≤ 0.3125]
… ≈ 0.6227
Out of 800 babies, around 498 will weigh less than 6 pounds.
3.
Pr[X > 5] = Pr[(X - 5.5)/1.6 > (5 - 5.5)/1.6]
… = Pr[Z > -0.3125]
… ≈ 0.6227
same as (2) due to the symmetry of the distribution (Z is centered at zero). Out of 800 babies, you can expect around 498 in this group.
4.
Pr[5.5 ≤ X ≤ 9] = Pr[(5.5 - 5.5)/1.6 ≤ (X - 5.5)/1.6 ≤ (9 - 5.5)/1.6]
… = Pr[0 ≤ Z ≤ 2.1875]
… ≈ 0.4857
Out of 800 babies, around 388 will weigh between 5.5 and 9 pounds.