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.
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.
They are a simple measure of the spread of the data, which is not affected by extreme values.
It is a value which appears not to fit in with the other data elements.
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.