Determine whether the represented
data is symmetric, right skewed, or left skewed.
What exactly does it mean to be
skewed? Well, a distribution that is not
symmetric must have values that tend to be more spread out on one side than the
other. Here would be an example of a
distribution that is not skewed. It relatively follows the normal
bell-shaped curve. Here would be an example of the
distribution being skewed left and an example being skewed right.
So we want to determine whether the
represented data is symmetric, right skewed, or left skewed. So our middle example would be
symmetric. This would be considered left
skewed. And to be left skewed means the
mean and the median are less than the mode. And over here to the right would be
the right skewed. And when we have a data set that is
skewed at right or right skewed, the mean and the median are greater than the
A good way to remember this is that
the ends kind of look like a tail. And notice with our data set, our
tail is on the left, just like the left skewed representation. Therefore, we will consider this
data to be left skewed.