For each [tex]1\le i\le n[/tex], [tex]E[X_i]=0[/tex], so that
[tex]\displaystyle E[Y_1]=E\left[\frac1n\sum_{i=1}^nX_i\right]=\frac1n\sum_{i=1}^nE[X_i]=0[/tex]
Meanwhile,
[tex]\displaystyle E[Y_2]=\frac1n\sum_{i=1}^nE[|X_i|][/tex]
Each of the [tex]X_i[/tex] have PDF
[tex]f_{X_i}(x)=\dfrac1{\sqrt{2\pi}}e^{-x^2/2}[/tex]
for [tex]x\in\Bbb R[/tex]. From this we get
[tex]E[|X_i|]=\displaystyle\frac1{\sqrt{2\pi}}\int_{-\infty}^\infty|x|e^{-x^2/2}\,\mathrm dx=\sqrt{\frac2\pi}\int_0^\infty xe^{-x^2/2}\,\mathrm dx=\sqrt{\frac2\pi}[/tex]
[tex]\implies E[Y_2]=n\sqrt{\dfrac2\pi}[/tex]
