For each probability, transform the normal random variable <em>X</em> with mean 19 and s.d. 4.04 to a standard normal random variable <em>Z</em> with mean 0 and s.d. 1, using the rule
<em>Z</em> = (<em>X</em> - 19) / 4.04
(a) Pr[15 ≤ <em>X</em> ≤ 20] = Pr[(15 - 19)/4.04 ≤ (<em>X</em> - 19)/4.04 ≤ (20 - 19)/4.04]
… ≈ Pr[-0.9901 ≤ <em>Z</em> ≤ 0.2475]
… ≈ Pr[<em>Z</em> ≤ 0.2475] - Pr[<em>Z</em> ≤ -0.9901]
(since <em>Z</em> is a continuous random variable)
… ≈ 0.4367
(b) Pr[<em>X</em> > 20] = Pr[(<em>X</em> - 19)/4.04 > (20 - 19)/4.04]
… ≈ Pr[<em>Z</em> > 0.2475]
… ≈ 1 - P[<em>Z</em> ≤ 0.2475]
(taking the complement probability)
… ≈ 0.4023
(c) Pr[<em>X</em> < 15] = 1 - Pr[15 ≤ <em>X</em> ≤ 20] - Pr[<em>X</em> > 20]
(also taking the complement)
… ≈ 0.1611