Linked from

The 16 pages that link to Outlier, each with the reason it gives.

• Arithmetic meanRelated: Because every value enters the sum, an outlier can pull the mean substantially.

• CorrelationRelated: A few extreme observations can substantially change Pearson correlation.

• Exploratory data analysisRelated: Investigating unusual observations can expose errors, rare cases, or meaningful variation.

• StandardizationRelated: Outliers can shift the mean and standard deviation that set the transformation.

• ResidualRelated: A large residual can flag an observation for closer investigation.

• Robust statisticsRelated: Outliers are a central source of sensitivity that robust methods aim to control.

• Descriptive statisticsRelated: Extreme observations can strongly affect summaries such as the mean and range.

• Reference rangeRelated: Unusual reference-sample results can distort estimated limits if handled poorly.

• Pearson correlation coefficientRelated: A single extreme point can substantially change Pearson correlation.

• Black swan theoryRelated: Black swan events stand apart from ordinary expectations and historical patterns.

• Box plotRelated: Many box plots mark observations beyond the whiskers as outliers.

• Correlation coefficientRelated: Extreme values can substantially alter coefficients calculated from raw measurements.

• KurtosisRelated: Because deviations are raised to the fourth power, a single outlier can dominate sample kurtosis.

• Stem-and-leaf displayRelated: Isolated leaves can make unusually extreme observations visible.

• Violin plotRelated: A density shape may obscure isolated observations unless raw points or marks are added.

• 68–95–99.7 ruleRelated: Under a normal model, observations beyond three standard deviations are rare according to the rule.