Hajuvusmõõdikud

Hajuvusmõõdikud, also known as dispersal metrics, are tools used to quantify how spread out or dispersed a set of data points is. These metrics provide a measure of the variability or scatter within a dataset, helping to understand the distribution of values.

One of the most common hajuvusmõõdikud is the range, which is the difference between the maximum and minimum values in a dataset. While simple to calculate, the range is sensitive to outliers and does not consider the distribution of values in between.

Another widely used measure is the variance. Variance quantifies the average of the squared differences from the mean. It is a fundamental concept in statistics, but its unit is the square of the original data unit, making it less intuitive for direct interpretation.

The standard deviation, which is the square root of the variance, is a more interpretable measure as it is in the same unit as the original data. A small standard deviation indicates that data points tend to be close to the mean, while a large standard deviation suggests that data points are spread out over a wider range of values.

The interquartile range (IQR) is another important hajuvusmõõdik. It is the difference between the third quartile (75th percentile) and the first quartile (25th percentile) of a dataset. The IQR represents the spread of the middle 50% of the data and is less affected by extreme values than the range or standard deviation.

Other hajuvusmõõdikud include the mean absolute deviation, which calculates the average of the absolute differences from the mean, and coefficient of variation, which expresses the standard deviation as a percentage of the mean, allowing for comparison of variability between datasets with different units or scales. These metrics collectively offer a comprehensive understanding of data dispersion.