00:01
So when it comes to trying to identify the skewness of a distribution, it's helpful to think about, well, when we say something is being skewed, you can think of the way that we use that term in common english.
00:16
Somebody has a skewed perception.
00:18
Something is warping their perception in a particular direction.
00:22
So, when we talk about skewness, we're talking about effectively, basically, or it's, you can have an intuitive understanding of it, if you think of it as, how is the mean being biased? or how is the mean being skewed or warped? we know that the mean is sensitive to outliers.
01:07
So, if we have something like this, we have that the mean and, or pardon me, we have that the mode is at that peak there.
01:28
The median will be, you know, somewhere there.
01:36
The mean is being skewed to the right.
01:40
Hence why this is a right skewed or a positive skewed distribution.
01:47
Because we have this long tail of outliers to the right, we have that the mean is being pulled rightwards.
01:55
It's being distorted or skewed rightwards.
01:58
Similarly, if we have a long tail to the left, we have that the relationships will be flipped around.
02:21
So, we have a left, such negative skew...