Outlier Essential terms you should know.

Outlier A Term You Need to Know

An outlier is a value in a data set that lies significantly away from other values in the same data set. Outliers can occur due to measurement error, data entry error, or simply because the value represents an unusual or exceptional observation. Outliers can have a large impact on the mean and other measures of central tendency and spread in a data set, and can affect the validity of inferences made from the data.

Outliers can be identified by visual inspection of a scatter plot or by using statistical methods such as the interquartile range (IQR) or Z-scores. The IQR is calculated as the difference between the 75th and 25th percentiles, and values that fall outside of the range defined by 1.5 times the IQR are considered outliers. Z-scores are calculated by transforming the data values to standard deviations from the mean, and values with a Z-score greater than 3 or less than -3 are considered outliers.

It is important to carefully consider outliers when analyzing a data set, as they can have a major impact on the results of statistical tests and inferences made from the data. Outliers may need to be removed or transformed in order to obtain accurate results, but in some cases they may also provide important information about the data set and should not be removed.

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