Which of the following statements is true regarding positive skewness?

In the context of positive skewness, the statement indicating that the bulk of data values are concentrated on the left is accurate. Positive skewness means that the tail on the right side of the distribution is longer or fatter than the left side. This results in a distribution where most of the data points lie to the left of the mean, with fewer data points extending toward the higher values on the right.

In a positively skewed distribution, while the majority of the values cluster on the lower end, they drag the mean to the right of the median. Therefore, it’s also true that the mean is greater than the median in such distributions. However, the consistent characteristic of positive skewness is the left concentration of the data values, which validates the correctness of that statement.

The alternative choices suggest different relationships between mean, median, and mode, as well as a symmetrical distribution, which do not hold true in a positively skewed scenario. In summary, the clear characteristic of having the bulk of data clustered on the left, while the right side tail extends, affirms the truthful nature of the chosen statement about positive skewness.