This post is almost entirely inaccurate re: actual statistics. Power, as you say, is the likelihood of a given experiment rejecting the null hypothesis given so

This post is almost entirely inaccurate re: actual statistics. Power, as you say, is the likelihood of a given experiment rejecting the null hypothesis given some a priori sample size and effect size. And one- vs. two-tailed tests do not change effect sizes, or even your estimate of the variability surrounding an effect, but a p-value related to the effect (should you choose to calculate one). You would think, given their team of "analysts" and "statisticians", that they might have known these basic pieces of statistics.