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.
They are called outliers
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
Go into your data to determine which values are outliers and if they're significant and random (not an apparent group), eliminate them. This will take them out of your boxplot.
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.
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.