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Extreme data refers to data points that fall significantly outside the range of other observations in a dataset. These outliers can skew statistical analyses and distort the interpretation of results. Extreme data can be caused by measurement errors, natural variability, or rare events, and it is important to identify and properly handle these outliers in order to ensure the accuracy and reliability of data analysis.
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Professor
Jordan
FranThere are three dimensions to Extreme Data - volume, velocity, and variety, - and management of these dimensions is critical when it comes to winning the battle for control of enterprise data amid the conflicting requirements of business intelligence and reporting vs. data mining and statistical analysis. Management of the data is often part of an Information Lifecycle Management strategy (ILM) or Nearline approach.
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Extreme numbers compared to the rest of the data are called?
Extreme numbers in the data as compared the the rest of the data are called OUTLIERS.
Why it is useful to fiNd the meaN mediaN aNd mode of a set of data?
when there are extreme values in the data
When data points in a set of a data are extreme enough to have a significant effect on the mean what are they called?
Such a data point is called an outlier.
Extreme value within a data set?
It is a value which appears not to fit in with the other data elements.
HOW are quartiles helpful in describing data?
They are a simple measure of the spread of the data, which is not affected by extreme values.
