Anomalous Data
Mean- If there are no outliers. A really low number or really high number will mess up the mean. Median- If there are outliers. The outliers will not mess up the median. Mode- If the most of one number is centrally located in the data. :)
Values that are either extremely high or low in a data set are called 'outliers'. They are typically 3 standard deviations or more from the mean.
It is not.
Outliers are basically numbers, in a set of numbers, that don't belong in that set and/or that stand out. For example, in the data set {3, 5, 4, 4, 6, 2, 25, 5, 6, 2} the value of 25 is an outlier. For a set of numerical data (a set of numbers), any value (number) that is markedly smaller or larger than other values is an outlier. This is the qualitative definition. Mathematically, a quantitative definition often given is that an outliers is any number that is more than 1.5 times the interquartile range away from the median. However, this is not definitive and in some cases other definitions will be used.
They are called extreme values or outliers.
They are called outliers
If the data numbers are all really close together than no. But if the data has numbers; for example: 12,43,45,51,57,62,90 (12 and 90 are the outliers) which are really far aprt, than yes.
In chemistry, outliers are data points that deviate significantly from the rest of the data set. Outliers can result from measurement errors, experimental uncertainties, or unexpected reactions. It is important to identify and address outliers in data analysis to ensure accurate and reliable results.
Anomalous Data
Yes, it is.
Grubbs test is used to detect outliers in a univariate data set.
No. Outliers are part of the data and do not affect them. They will, however, affect statistics based on the data and inferences based on the data.
Mean- If there are no outliers. A really low number or really high number will mess up the mean. Median- If there are outliers. The outliers will not mess up the median. Mode- If the most of one number is centrally located in the data. :)
an outliers can affect the symmetry of the data because u can still move around it
to organize your data set and figure out mean, median, mode, range, and outliers.
Values that are either extremely high or low in a data set are called 'outliers'. They are typically 3 standard deviations or more from the mean.