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

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

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!

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

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)

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