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The Pearson skew is a measure of asymmetry of a distribution, based on the difference between the mean and the median of a distribution. Here we show how to calculate the Pearson skew, estimate its standard error and the confidence interval. The derivation is based on a population following a normal distribution. Simulations explored the validity of this expression when the normality assumption is met in comparison to when the normality assumption is not met. The standard error of the Pearson skew revealed very robust in case of non-normal populations, compared to the Fisher Skew as presented in Harding, Tremblay and Cousineau (2014).