Central tendency is a fundamental concept in statistics that describes the center point or typical value of a dataset. It helps in summarizing data sets with a single value that represents the entire data. The three main measures of central tendency include mean, median, and mode.

The main measures of central tendency are: Mean (Average): The sum of all data points divided by the number of points. Median: The middle value when data points are arranged in ascending or descending order. Mode: The most frequently occurring value in a dataset.

You should use the mean (average) when you want to find the overall average of a dataset and there are no extreme values (outliers) that could skew the result. The mean helps get a general idea of your data's "central" value when all values are similar. For example, if you want to know the average test score of a class where most students scored similarly, the mean is a good measure to use.

The median is used when you need the middle value of a dataset, especially if there are outliers. It’s ideal for skewed data, like income, to avoid distortion by extreme values.

The mode is ideal for categorical data or when identifying the most common value in a dataset. It is beneficial when data is not numerical.

The weighted mean assigns different weights to data points based on their importance, while the standard mean treats all data points equally. The weighted mean is calculated by multiplying each data point by its corresponding weight, adding these products together, and then dividing by the total sum of the weights.