Extreme data refers to data points that exist at the outer edges of a dataset, often representing rare or unusual events. This type of data can include outliers, anomalies, or extreme values that can significantly influence statistical analyses and modeling. Analyzing extreme data is crucial in fields like finance, insurance, and climate science, where understanding rare events can inform risk assessment and decision-making. Properly handling extreme data is essential to avoid misleading conclusions in research and applications.
Extreme numbers in the data as compared the the rest of the data are called OUTLIERS.
when there are extreme values in the data
Such a data point is called an outlier.
It is a value which appears not to fit in with the other data elements.
They are a simple measure of the spread of the data, which is not affected by extreme values.
Extreme numbers in the data as compared the the rest of the data are called OUTLIERS.
Extreme test data is data that is on the boundary. eg if you were asked to enter an age between 1 - 100 extreme test data would be 0 and 101 It is on the boundary of normal test data (Normal test data is within the boundary) Hope i could help
median
To find the lower extreme, you need to identify the smallest value in a data set. To find the upper extreme, you need to identify the largest value in the data set. These values represent the lowest and highest points of the data distribution.
when there are extreme values in the data
They are called extreme values or outliers.
Outlier
Such a data point is called an outlier.
They are a simple measure of the spread of the data, which is not affected by extreme values.
No because an outlier is an extreme data point that can almost be ignored.
It is a value which appears not to fit in with the other data elements.
A data display that organizes data values into four parts using the lower extreme,lower quartile,median,upper quartile,and upper extreme.