which central tendency is relevant in incomplete distribution
Answers
The central tendency of a distribution represents one characteristic of a distribution. Another aspect is the variability around that central value. While measures of variability is the topic of a different article (link below), this property describes how far away the data points tend to fall from the center. The graph below shows how distributions with the same central tendency (mean = 100) can actually be quite different. The panel on the left displays a distribution that is tightly clustered around the mean, while the distribution on the right is more spread out. It is crucial to understand that the central tendency summarizes only one aspect of a distribution and that it provides an incomplete picture by itself.
Measures of central tendency are very useful in Statistics. Their importance is because of the following reasons: (i) To find representative value: Measures of central tendency or averages give us one value for the distribution and this value represents the entire distribution.