Kvartili

Kvartili are statistical measures that divide a dataset into four equal parts. They are a type of quantile, similar to a median which divides data into two parts. The first quartile (Q1) is the value below which 25% of the data falls. The second quartile (Q2) is the median, meaning 50% of the data falls below this value. The third quartile (Q3) is the value below which 75% of the data falls.

To calculate quartiles, the dataset must first be sorted in ascending order. Q2, the median, is found by identifying the middle value. If there is an even number of data points, the median is the average of the two middle values. Q1 is the median of the lower half of the data, excluding the median itself if the dataset has an odd number of points. Similarly, Q3 is the median of the upper half of the data.

Kvartili are useful for understanding the spread and distribution of data. The difference between Q3 and Q1, known as the interquartile range (IQR), represents the middle 50% of the data and is less sensitive to outliers than the total range. Quartiles can also be used to identify potential outliers, which are values that lie far outside the typical range of the data, often defined as being more than 1.5 times the IQR below Q1 or above Q3. They are a fundamental concept in descriptive statistics and are widely used in various fields to summarize and analyze data.