Skewness
Also known as: skew, distribution skew
Grade 9-12
A measure of the asymmetry of a distribution — how much it leans to one side of the mean. Skewness tells you whether the mean or median is a better measure of center.
Definition
A measure of the asymmetry of a distribution — how much it leans to one side of the mean.
💡 Intuition
A right-skewed distribution has a long tail to the right (a few very large values); left-skewed has a long tail to the left.
🎯 Core Idea
Positive skew: tail on right, mean > median. Negative skew: tail on left, mean < median.
Example
Formula
🌟 Why It Matters
Skewness tells you whether the mean or median is a better measure of center.
Related Concepts
🚧 Common Stuck Point
Positive skewness means the tail extends to the right, not that most values are large.
Frequently Asked Questions
What is Skewness in Statistics?
A measure of the asymmetry of a distribution — how much it leans to one side of the mean.
Why is Skewness important?
Skewness tells you whether the mean or median is a better measure of center.
What do students usually get wrong about Skewness?
Positive skewness means the tail extends to the right, not that most values are large.
What should I learn before Skewness?
Before studying Skewness, you should understand: distribution shape.
Prerequisites
Next Steps
How Skewness Connects to Other Ideas
To understand skewness, you should first be comfortable with distribution shape. Once you have a solid grasp of skewness, you can move on to mean vs median.