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Say you have a random variable $X$ (e.g., kilometers driven). Getting its variance is straightforward. But what if you want to say, $A$ percent of the variance in $X$ is due to $\text{Var}(X)$ for female drivers and $B$ percent is the rest, that is, $\text{Var}(X)$ for male drivers? $A + B$ should be 100 percent.

Is this possible? Are there assumptions to be made to simplify things? Independence of female and male drivers?

[Question was also asked here https://mathoverflow.net/questions/88185/variance-decomposition-anova but I realized it's best to do it at Stats instead.]

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  • $\begingroup$ I would suggest you remove the duplicate on MathOverflow. $\endgroup$
    – chl
    Commented Feb 12, 2012 at 8:58

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This is pretty much what analysis of variance (ANOVA) does. Except that there is an additional source of variance in the response variable which is variation between individuals that is not explained by sex.

A model is fit of the form:

$y_i=\beta_0+\beta_1x_i+\epsilon_i$

where $x_i$ is 1 if the individual is male, 0 otherwise; and $\epsilon_i$ has a normal distribution. It is then possible to divide the variance into an element explained by the difference between sexes (the structural part of the model above) and an element explained by the difference between individuals (the $\epsilon_i$ part).

It's not possible to say what variance is explained by men and what by women - only a total amount explained by the difference between the two.

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    $\begingroup$ Did you want to add that not all of the variance will be explained by gender, e.g. some could be due to age, or quality of public transport. :) $\endgroup$
    – Michelle
    Commented Feb 11, 2012 at 10:35
  • $\begingroup$ Yes, good point, that was meant to be included in "variation between individuals that is not explained by sex", which should be broad enough... The point is a good one, that the remaining variance can still be thought of as having a truly random individual part, and a structural part that has just been missed from the under-specified model. $\endgroup$ Commented Feb 11, 2012 at 10:42
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Variance is one of true distribution characteristics indicating how widely values of given random variable are distributed. In a sense, it is a similar concept to width of range (difference between min and max) So in almost all cases, you can't say "A percent of the variance in X is due to the Var(X) for female drivers and B percent is the rest. A + B should be 100 percent" whether that variable is independent of gender.

If you want to run conventional ANOVA, then Peter Ellis's answer is the right approach. Otherwise, describe what you want to achieve in detail.

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  • $\begingroup$ Variance is not a statistic. $\endgroup$
    – cardinal
    Commented Feb 12, 2012 at 5:18

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