A positive skewness indicates that the positive \((x_k - \mu)^3\) terms (likewise \((x_k - \overline{x})^3\) terms) overwhelm the negative terms. So, a positive skewness indicates that the data set is strung out to the right. Likewise, a negative skewness indicates a data set that is strung out to the left.