Left skewed distribution

1. What does a left skewed distribution mean?
2. What is an example of a left skewed distribution?
3. What causes a left skewed distribution?
4. Does skewed left mean negative?

What does a left skewed distribution mean?

In statistics, a negatively skewed (also known as left-skewed) distribution is a type of distribution in which more values are concentrated on the right side (tail) of the distribution graph while the left tail of the distribution graph is longer.

What is an example of a left skewed distribution?

An example of a real life variable that has a skewed left distribution is age of death from natural causes (heart disease, cancer, etc.). Most such deaths happen at older ages, with fewer cases happening at younger ages.

What causes a left skewed distribution?

Skewed data often occur due to lower or upper bounds on the data. That is, data that have a lower bound are often skewed right while data that have an upper bound are often skewed left. Skewness can also result from start-up effects.

Does skewed left mean negative?

Negative skew refers to a longer or fatter tail on the left side of the distribution, while positive skew refers to a longer or fatter tail on the right. These two skews refer to the direction or weight of the distribution.