(17) From the plot, you see that
Pr[$15,500 ≤ x ≤ $18,500] = 99.7%
We can split up the probability on the left at the mean, so that
Pr[$15,500 ≤ x ≤ $17,000] + Pr[$17,000 ≤ x ≤ $18,500] = 99.7%
Any normal distribution is symmetric about its mean, so the two probabilities here are the same. The one on the left is what you want to compute. So you have
2 × Pr[$15,500 ≤ x ≤ $17,000] = 99.7%
==> Pr[$15,500 ≤ x ≤ $17,000] = 49.85%
(19) The mean of a normal distribution is also the median, so half the distribution lies to either side of the mean. Mathematically, we write
Pr[x ≥ $17,000] = 50%
The plot shows that
Pr[$16,500 ≤ x ≤ $17,500] = 68%
and by using the same reasoning as in (17), we have
Pr[$16,500 ≤ x ≤ $17,000] + Pr[$17,000 ≤ x ≤ $17,500] = 68%
2 × Pr[$17,000 ≤ x ≤ $17,500] = 68%
Pr[$17,000 ≤ x ≤ $17,500] = 34%
Now
Pr[x ≥ $17,000] = 50%
Pr[$17,000 ≤ x ≤ $17,500] + Pr[x ≥ $17,500] = 50%
34% + Pr[x ≥ $17,500] = 50%
==> Pr[x ≥ $17,500] = 16%
(21) From the plot,
Pr[$16,000 ≤ x ≤ $18,000] = 95%
This means (by definition of complement) that
Pr[x ≤ $16,000 or x ≥ $18,000] = 100% - 95% = 5%
and by symmetry,
Pr[x ≤ $16,000 or x ≥ $18,000] = 5%
Pr[x ≤ $16,000] + Pr[x ≥ $18,000] = 5%
2 × Pr[x ≤ $16,000] = 5%
==> Pr[x ≤ $16,000] = 2.5%