Skewed Probability Distribution
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A Skewed Probability Distribution is a probability value distribution that is a skewed distribution.
- AKA: Skewed Distribution, Imbalanced Distribution.
- Context:
- It can range from having a Positive Skew to having a Negative Skew.
- It can be associated to a Skewed Probability Function.
- Example(s):
- Counter-Example(s):
- See: Imbalanced Training Dataset, Mean, Bimodal Distribution.
References
2011
- (Wikipedia, 2011) ⇒ http://en.wikipedia.org/wiki/Skewness
- In probability theory and statistics, skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable. The skewness value can be positive or negative, or even undefined. Qualitatively, a negative skew indicates that the tail on the left side of the probability density functionis longer than the right side and the bulk of the values (including the median) lie to the right of the mean. A positive skew indicates that the tail on the right side is longer than the left side and the bulk of the values lie to the left of the mean. A zero value indicates that the values are relatively evenly distributed on both sides of the mean, typically but not necessarily implying a symmetric distribution.