What is the use of central tendency?

Answer 1

A central tendency is a number that expresses something "central" about a sample of values (which could be test scores, temperatures, etc...). Measures of central tendency include the mean, the median, and the mode.
The Mean is equal to the average of all the values. Thus, the Mean is equal to the sum of all the values (add them all up) divided by the total number of values in your set or sample. This average tells you nothing about what your highest and lowest values are (the range). However, ...
The Median is equal to the the number which, if you were to arrange your values from lowest to highest, falls exactly in the middle of your distribution of values. So, if you have 41 values, for instance, the Median would be the 21st value, and there would be 20 values equal to or smaller than the Median, and 20 values equal to or larger than the median. If, on the other hand, there were 100 values, the median would be the average of the 50th and 51st values in the distribution. The median tells you nothing, however, about what values occur "most often" in your distribution. So....
There is the mode, which is equal to the value which occurs most often in your distribution. Simply count how many times each of your values occurs, and the mode= the one that occurs most often. The following is an example of a distribution which is highly "skewed" meaning that there are differences between the mean, median and mode for the set of values being observed.

Mean
The mean is the most commonly-used measure of central tendency. When we talk about an "average", we usually are referring to the mean. The mean is simply the sum of the values divided by the total number of items in the set. The result is referred to as the arithmetic mean.
It is the best average of measures of central tendency.
It is used in Stock exchange, Market to calculate the Mean (share) Price in the particular day.
Sometimes it is useful to give more weighting to certain data points, in which case the Median
The median is determined by sorting the data set from lowest to highest values and taking the data point in the middle of the sequence. There is an equal number of points above and below the median. For example, in the data set {1,2,3,4,5} the median is 3; there are two data points greater than this value and two data points less than this value. In this case, the median is equal to the mean. But consider the data set {1,2,3,4,10}. In this dataset, the median still is three, but the mean is equal to 4. If there is an even number of data points in the set, then there is no single point at the middle and the median is calculated by taking the mean of the two middle points.
The median can be determined for ordinal data as well as interval and ratio data. Unlike the mean, the median is not influenced by outliers at the extremes of the data set. For this reason, the median often is used when there are a few extreme values that could greatly influence the mean and distort what might be considered typical. This often is the case with home prices and with income data for a group of people, which often is very skewed. For such data, the median often is reported instead of the mean. For example, in a group of people, if the salary of one person is 10 times the mean, the mean salary of the group will be higher because of the unusually large salary. In this case, the median may better represent the typical salary level of the group. Mode
The mode is the most frequently occurring value in the data set. For example, in the data set {1,2,3,4,4}, the mode is equal to 4. A data set can have more than a single mode, in which case it is multimodal. In the data set {1,1,2,3,3} there are two modes: 1 and 3.
The mode can be very useful for dealing with categorical data. For example, if a sandwich shop sells 10 different types of Sandwiches, the mode would represent the most popular sandwich. The mode also can be used with ordinal, interval, and ratio data. However, in interval and ratio scales, the data may be spread thinly with no data points having the same value. In such cases, the mode may not exist or may not be very meaningful.
We have to findout Model value of the particular things.
For example shoe Model size =Maximum no of persons used shoe size,
likewise shirt size and various products models.
When to use Mean, Median, and Mode
The following table summarizes the appropriate methods of determining the middle or typical value of a data set based on the measurement scale of the data.

Measurement Scale
Best Measure of the "Middle"
Nominal
(Categorical)
Mode
Ordinal
Median
Interval
Symmetrical data: Mean
Skewed data: Median
Ratio
Symmetrical data: Mean
Skewed data: Median

result is called the weighted arithmetic mean