Unformatted text preview: variable X , and that the mean μ , exists (and is ﬁnite). We would like to measure how far a “typical” value of X is from μ . One way to measure this distance is ( Xμ ) 2 ; we square the diﬀerence so as to measure all distances as positive. The expected value of this quantity is V ( X ) = Z ∞∞ ( xμ ) 2 f ( x ) dx. This quantity is called the variance, and is the expected value of the squared distance to μ . The standard deviation , denoted σ , is the square root of the variance. By taking...
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 Spring '07
 JonathanRogawski
 Math, Calculus, Normal Distribution, Variance, Probability theory, probability density function

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