Trimmed Mean
Candlefocus EditorThe trimmed mean is similar to the traditional mean, or average, except that it excludes a small designated percentage of the largest and smallest values from the calculation. This removes outliers from being able to greatly affect the value of the mean, providing a smoother measure of the data.
For example, using the trimmed mean inflation rate, which eliminates the upper and lower 4% of the data points, can give a truer picture of the rate of inflation. The traditional mean would include the outliers—for instance, seasonal shopping or investment trends—which could give an overly optimistic or pessimistic inference about the inflation rate.
The trimmed mean is also used in the analysis of other economic measures, such as income and production. For example, if too few, or too many, income levels fall too far from the average, they may disproportionately affect the value of the traditional mean, thus providing an inaccurate measure.
Finally, the trimmed mean helps in providing a basis for comparison between different groups or regions. Otherwise, the presence of extreme outliers can imply false correlation between the groups, making it difficult to make accurate conclusions.
Trimmed means are an important tool in economic statistics. By removing the influence of outliers, they provide a more realistic image of the data, an important factor that must be taken into account in order to make sound decisions and draw sound conclusions.