Graphic linear regression process that makes it possible to find the parameters of a line of regression by using the median of the data in a distribution.

The median-median method is most often used when the distribution has a large quantity of data and is particularly effective when this distribution includes inconsistent data. This method has several steps:

- Arranging the points so that the x values are in ascending order (if two
*x*values are identical, they are ordered based on the*y*value); - Separating the points on the scatter plot into three groups of equal frequencies (so that the difference between the number of data in each group is minimal);
- For each group, determining the median of the x coordinates and the median of the y coordinates M
_{1}(*x, y*), M_{2}(*x, y*) and M_{3}(*x, y*); - Determining the mean of the x coordinates and the mean of the y coordinates of the three median points: P
_{1}(\(\overline{x}, \overline{y}\) - Positioning the coordinate points M
_{1}(*x, y*) and M_{3}(*x, y*) and drawing a line through them; - The line of regression is parallel to the line that passes through the points M
_{1}(*x, y*) and M_{3}(*x, y*); - The line of regression passes through the point P
_{1}(\(\overline{x}, \overline{y}\)); - The y-intercept P
_{2}(0, y) of the line of regression is calculated using the point P_{1}(\(\overline{x}, \overline{y}\)) and the slope of the line that passes through M_{1}(*x, y*) and M_{3}(*x, y*).