A distribution is positively skewed when the mean is:

A positively skewed distribution is characterized by the bulk of the data points being clustered towards the lower end of the range, with a tail that extends toward the higher end. In such a distribution, the mean is affected by the presence of outliers or a longer tail on the higher side, which pulls the mean toward that side.

When a distribution is positively skewed, the mean is typically greater than the median and is shifted to the right of the median. This rightward shift occurs because the higher values, though fewer in number, have a significant influence on the average (the mean) due to their magnitude. Therefore, in a positively skewed distribution, it is accurate to state that the mean is shifted to the right.

The other options do not accurately describe the behavior of the mean in a positively skewed distribution. Bimodal and multimodal refer to distributions with multiple peaks, which do not inherently imply skewness. The notion of a shift to the left is characteristic of negatively skewed distributions, where the mean is influenced by lower values. Thus, the correct description is that the mean is shifted to the right in a positively skewed distribution.