Measures of central tendency are statistical measures that provide information about the center or average value of a dataset. The three commonly used measures of central tendency are the mean, median, and mode.
- Mean: The mean is the most common measure of central tendency. It is calculated by summing up all the values in a dataset and dividing the sum by the total number of values. The formula for the mean is:
Mean = (Sum of all values) / (Total number of values)
The mean is sensitive to extreme values and can be influenced by outliers. It is suitable for data that follows a roughly symmetric distribution.
- Median: The median is the middle value in a dataset when it is arranged in ascending or descending order. In other words, it is the value that separates the lower half from the upper half of the data. If there is an even number of values, the median is calculated by taking the average of the two middle values.
The median is less affected by extreme values or outliers compared to the mean. It is a robust measure of central tendency and is suitable for skewed or non-normal distributions.
- Mode: The mode is the value or values that appear most frequently in a dataset. In some cases, there may be multiple modes or no mode at all. Unlike the mean and median, the mode can be used for both numerical and categorical data.
The mode is useful for identifying the most common category or value in a dataset. It is often used to describe qualitative or nominal data.
Each measure of central tendency has its own strengths and applications. The choice of which measure to use depends on the nature of the data and the specific objectives of the analysis.