If skewness is positive, the data are positively skewed or skewed right, meaning that the right tail of the distribution is longer than the left. If skewness is negative, the data are negatively skewed or skewed left, meaning that the left tail is longer. If skewness = 0, the data are perfectly symmetrical.
In respect to this, what does it mean to be skewed to the right?
For a right skewed distribution, the mean is typically greater than the median. Also notice that the tail of the distribution on the right hand (positive) side is longer than on the left hand side.
What is positive and negative skewness?
A distribution is skewed if one of its tails is longer than the other. The first distribution shown has a positive skew. This means that it has a long tail in the positive direction. The distribution below it has a negative skew since it has a long tail in the negative direction.
What does it mean if the mean is greater than the median?
But if a distribution is skewed, then the mean is usually not in the middle. Notice that in this example, the mean is greater than the median. This is common for a distribution that is skewed to the right (that is, bunched up toward the left and with a "tail" stretching toward the right).