**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).