Measures of central tendency are statistical measures that provide a single value to summarize the centre or midpoint of a dataset. The three main measures of central tendency are:

Arithmetic Mean

The mean is the most commonly used measure of central tendency. It is calculated by adding up all the values in a dataset and then dividing by the number of values. The mean is sensitive to extreme values, also known as outliers. Mean can be Calculated in Individual , Discrete and Continuous Series by Direct Method , Short Cut Method and Step Deviation Method.

There are Two Types of Arithmetic Mean Simple Arithmetic Mean and Weighted Arithmetic Mean. We can find simple by Adding the Values of all the items of a Series and Diving the total by the number of items like.

1. Summation: Add up all the individual values in the dataset.
2. Division: Divide the sum by the total number of values in the dataset.

The mean is sensitive to extreme values, often called outliers, as it takes into account every value in the dataset. When the dataset is symmetrically distributed, the mean tends to be close to the median. However, in skewed distributions or in the presence of outliers, the mean may not accurately represent the central tendency of the data.

We can find Practically the Mean in Central Tendency as such.