where @math{x_i} are the elements of the dataset data. For samples drawn from a gaussian distribution the variance of @math{\Hat\mu} is @math{\sigma^2 / N}.
where @math{x_i} are the elements of the dataset data. Note that the normalization factor of @math{1/(N-1)} results from the derivation of @math{\Hat\sigma^2} as an unbiased estimator of the population variance @math{\sigma^2}. For samples drawn from a gaussian distribution the variance of @math{\Hat\sigma^2} itself is @math{2 \sigma^4 / N}.
This function computes the mean via a call to gsl_stats_mean
. If
you have already computed the mean then you can pass it directly to
gsl_stats_variance_m
.