CENTRAL TENDENCY ECONOMETRICS|L-14|

A central tendency (or measure of central tendency) is a central or typical value for a probability distribution.

Colloquially, measures of central tendency are often called averages. The term central tendency dates from the late 1920s.

The most common measures of central tendency are the arithmetic mean, the median, and the mode. A middle tendency can be calculated for either a finite set of values or for a theoretical distribution, such as the normal distribution. Occasionally authors use central tendency to denote “the tendency of quantitative data to cluster around some central value.”

The central tendency of a distribution is typically contrasted with its dispersion or variability; dispersion and central tendency are the often characterized properties of distributions. Analysis may judge whether data has a strong or a weak central tendency based on its dispersion.

What is Dispersion?

In statistics, dispersion is a measure of how distributed the data is meaning it specifies how the values within a data set differ from one another in size. It is the range to which a statistical distribution is spread around a central point. It mainly determines the variability of the items of a data set around its central point. Simply put, it measures the degree of variability around the mean value. The measures of dispersion are important to determine the spread of data around a measure of location. For example, the variance is a standard measure of dispersion which specifies how the data is distributed about the mean. Other measures of dispersion are Range and Average Deviation.

What is Skewness?

Skewness is a measure of asymmetry of distribution about a certain point. A distribution may be mildly asymmetric, strongly asymmetric, or symmetric. The measure of asymmetry of a distribution is computed using skewness. In case of a positive skewness, the distribution is said to be right-skewed and when the skewness is negative, the distribution is said to be left-skewed. If the skewness is zero, the distribution is symmetric. Skewness is measured on the basis of Mean, Median, and Mode. The value of skewness can be positive, negative, or undefined depending on whether the data points are skewed to left, or skewed to the right.