There is no agreed definition of an outlier and consequently, there is no simple answer to the question. The number of outliers will depend on the criterion used to identify them.
If you have observations from a normal distribution, you should expect around 1 in 22 observations to be more than 2 standard deviations from the mean, and about 1 in 370 more than 3 sd away. You will have more outliers if the distribution is non-normal - particularly if it is skewed.
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They are called outliers
Data that does not fit with the rest of a data set is known as an outlier. Outliers can skew statistical analyses and distort the interpretation of data. They can be caused by errors in data collection, measurement variability, or may represent true but rare occurrences in the data set. Identifying and handling outliers appropriately is crucial in ensuring the accuracy and reliability of data analysis results.
an outliers can affect the symmetry of the data because u can still move around it
Each outlier is a single point in the outcome space.
Outliers
There is no limit to the number of outliers there can be in a set of data.
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.
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. :)
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.
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.