Understanding Positive Skewness

Skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable. It indicates whether the data points in a distribution are skewed towards the left, right, or are symmetric. A positive skew indicates that there are more data points on the left side of the distribution, with a long tail on the right. Conversely, a negative skew indicates that there are more data points on the right side, with a long tail on the left. Kurtosis, on the other hand, measures the 'tailedness' of the distribution, indicating how heavy or light the tails are relative to a normal distribution.

Given this information, which of the following statements is true regarding skewness?