szélsértékek

Szélsértékek, often translated as "extreme values" or "outliers," refers to data points that deviate significantly from the majority of other observations in a dataset. These values can arise from various sources, including measurement errors, data entry mistakes, or genuine rare occurrences. Identifying and understanding szélsértékek is crucial in statistical analysis as they can disproportionately influence the results of calculations like the mean, standard deviation, and correlation.

There are several methods for detecting szélsértékek. Visual inspection of data plots, such as box plots or scatter plots, can often reveal extreme values. Statistical methods include using z-scores, where a value is considered an outlier if its z-score exceeds a certain threshold (commonly 2 or 3), or using the interquartile range (IQR) method, where values falling below Q1 - 1.5*IQR or above Q3 + 1.5*IQR are flagged.

The decision of how to handle szélsértékek depends on their cause and the goals of the analysis. In some cases, extreme values may be corrected if they are due to identifiable errors. In other situations, they might be removed from the dataset, especially if they are clearly erroneous or if the analysis is sensitive to their presence. However, it's also important to consider that outliers can sometimes represent important phenomena or genuine variations in the data, and their removal should be carefully justified. Analyzing the data with and without the szélsértékek can provide a more comprehensive understanding of the dataset's characteristics.