Symmetry Properties of the Standard Normal Distribution

Use the symmetry of the standard normal distribution about 0 to compute probabilities of the form P(Z<z)P(Z < -z), P(z<Z<z)P(-z < Z < z), and P(a<Z<b)P(a < Z < b) when the interval crosses zero, given values of P(Z<z)P(Z < z) for z>0z > 0.

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Symmetry of the Standard Normal

The probability density function of the standard normal distribution ZN(0,1)Z \sim N(0,1) is symmetric about 00. That is,

ϕ(z)=ϕ(z)\phi(-z) = \phi(z)

for every real number z.z.

This symmetry means the area under the curve to the left of z-z equals the area to the right of +z:+z{:}

P(Z<z)  =  P(Z>z)  =  1P(Z<z).P(Z < -z) \;=\; P(Z > z) \;=\; 1 - P(Z < z).

As a special case, since the total area is 11 and the curve is symmetric about 0,0,

P(Z<0)  =  P(Z>0)  =  0.5.P(Z < 0) \;=\; P(Z > 0) \;=\; 0.5.

For example, given that P(Z<1)=0.8413,P(Z < 1) = 0.8413, we can find P(Z<1)P(Z < -1) without consulting a new table entry:

P(Z<1)  =  1P(Z<1)  =  10.8413  =  0.1587.P(Z < -1) \;=\; 1 - P(Z < 1) \;=\; 1 - 0.8413 \;=\; 0.1587.

This is why standard zz-tables only list values for z0z \geq 0 — the negative side is recovered by symmetry.

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