Mean is [tex] \mu=100 [/tex] and a standard deviation is [tex] \sigma =15 [/tex], then the variable [tex] X\sim N(100,15^2) [/tex].
Use substitution
[tex] Z=\dfrac{X-\mu}{\sigma},\\ \\ Z=\dfrac{X-100}{15} [/tex].
This substitution gives you that [tex] Z\sim N(0,1) [/tex].
a. For X=130, [tex] Z=\dfrac{130-100}{15}=2 [/tex] and [tex] Pr(X>130)=Pr(Z>2) =0.9772[/tex] (the decimal value is taken from the Standard Normal Distribution Table).
b. For X=90, [tex] Z=\dfrac{90-100}{15}=-\dfrac{2}{3} [/tex] and for X=110, [tex] Z=\dfrac{110-100}{15}=\dfrac{2}{3} [/tex]. Then [tex] Pr(90<X<110)=Pr\left(-\dfrac{2}{3}<Z<\dfrac{2}{3}\right)=0.2454-(-0.2454)=0.4908 [/tex] (the decimal value is taken from the Standard Normal Distribution Table).