The correct answer is: A. Skewed to the right
A skewed distribution is one in which the data points are not evenly distributed around the mean. In a skewed distribution, the mean, median, and mode are not all equal. The mean is the average of the data points, the median is the middle value of the data points, and the mode is the most frequent value in the data set.
In a skewed distribution, the mean is always pulled towards the tail of the distribution with the most data points. In a right-skewed distribution, the mean is pulled towards the right tail of the distribution, which means that there are more data points with higher values. In a left-skewed distribution, the mean is pulled towards the left tail of the distribution, which means that there are more data points with lower values.
In the case where the mean is less than the median, which is less than the mode, the distribution is right-skewed. This is because there are more data points with higher values, which pulls the mean towards the right. The median is still in the middle of the data set, but the mode is further to the left. This indicates that there are more data points with lower values, which is why the mode is less than the median.
Here is a diagram that illustrates the different types of skewness:
The normal distribution is a symmetrical distribution, which means that the mean, median, and mode are all equal. The right-skewed distribution is skewed to the right, which means that the mean is greater than the median and the mode. The left-skewed distribution is skewed to the left, which means that the mean is less than the median and the mode.