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Update lesson - possible correction #482

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Update lesson - possible correction #482

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2 changes: 1 addition & 1 deletion Statistical_Inference/Variance/lesson
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Expand Up @@ -133,7 +133,7 @@
Hint: Var(X_i) is the constant value sigma^2 and we're summing over n of them.

- Class: text
Output: So we've shown that Var(X')=Var(1/n*Sum(X_i))=(1/n^2)*Var(Sum(X_i))=(1/n^2)*Sum(sigma^2)=sigma^2/n for infinite populations when our samples are independent.
Output: So we've shown that Var(X')=Var(1/n*Sum(X_i))=(1/n^2)*Var(Sum(X_i))=(1/n^2)*n*(sigma)^2=sigma^2/n for infinite populations when our samples are independent.

- Class: text
Output: The standard deviation of a statistic is called its standard error, so the standard error of the sample mean is the square root of its variance.
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