diff --git a/source/ch-Expected-Value.ptx b/source/ch-Expected-Value.ptx
index ae04669..38170fe 100644
--- a/source/ch-Expected-Value.ptx
+++ b/source/ch-Expected-Value.ptx
@@ -538,9 +538,55 @@
Variance
- Text of section.
+ The expected value is one of several statistics sometimes referred to as a "measure of central tendency".
+ These are statistics that try to capture the "typical" value of the random variable.
+ Our next statistic tries to measure how spread out a distribution is.
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+ Let X be a random variable.
+ The variance of X is:
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+ \Var(X) = \E\left[ \left(X - \E(X)\right)^2 \right].
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+ This formula tries to capture some measure of how spread out the distribution is.
+ One way we might hope to measure spread is to calculate how far away X is from its expected value on average.
+ Squaring the term X - \E(X) ensures that any difference between the value of the random variable and its expected value contributes positively.
+ ("Distance away from" should be positive.) So, the formula in is conceptually clear.
+ In practice, there's another way to structure the formula that makes for cleaner calculation:
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+ Let X be a random variable.
+ Then:
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+ \Var(X) = \E\left(X^2\right) - \left(\E(X)\right)^2.
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+ \Var(X) \amp = \E\left[ \left(X - \E(X)\right)^2 \right]
+ \amp = \E\left[ X^2 - 2 \E(X) X + \left(\E(X)\right)^2\right]
+ \amp = \E\left(X^2\right) - 2 \E(X) \E(X) + \left(\E(X)\right)^2
+ \amp = \E\left(X^2\right) - \left(\E(X)\right)^2.
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