Data Analysis Outliers

THALES Project No. xxxx The Analysis of Outliers in Statistical Data Research Team Chrysseis Caroni, Associate Professor (P.I.) Vasiliki Karioti, Doctoral candidate

Outlier analysis is a much broader area, in which re-gression analysis is only asmallpart. NORMAL DATA NOISE ANOMALIES WEAK OR STRONG OUTLIERS Figure1.2.

Contextual outliers are detected using the values for the behavioral attributes in a specific context. Therefore, a data point might be an outlier in a given context

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Exploratory Data Analysis 1.3.5.17. Detection of Outliers: it may not be possible to determine if an outlying point is bad data. Outliers may be due to

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When we remove outliers we are changing the data, it is no longer “pure”, so we shouldn’t just get rid of the outliers without a good reason!

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Statistical outliers are data points that are far removed and numerically distant from the rest of the points.

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Analysis of data is a process of inspecting, cleansing, transforming, In the case of outliers: should one use robust analysis techniques?

Dictionary of Algorithms & Data; Digital Library of Mathematical Functions; Engineering Statistics Handbook; Federal Information Processing Standards (FIPS)

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Data Analysis is the process of systematically applying statistical and/or logical techniques to describe and illustrate, condense and recap, and evaluate data.

Aug 17, 2010 ยท Data Mining: Outlier analysis 1. Outlier Analysis
2. What are outliers?
Very often, there exist data objects that do not

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