Glossary

# Mean

Tags: Glossary

For a dataset, the mean is the sum of the observations divided by the number of observations.

## What is Mean?

The mean is a fundamental concept in statistics that helps us understand the central tendency of a dataset. It is a measure that represents the average value of a set of observations. To calculate the mean, we add up all the values in the dataset and then divide the sum by the total number of observations.

Let's consider a simple example to illustrate this concept. Imagine we have a dataset of five numbers: 2, 4, 6, 8, and 10. To find the mean of this dataset, we add up all the numbers: 2 + 4 + 6 + 8 + 10 = 30. Since there are five observations in total, we divide the sum by 5: 30 ÷ 5 = 6. Therefore, the mean of this dataset is 6.

The mean is a useful measure because it provides a single value that summarizes the dataset. It gives us an idea of the typical value or average value of the observations. However, it is important to note that the mean can be influenced by extreme values, also known as outliers. Outliers are observations that are significantly different from the other values in the dataset. These outliers can skew the mean and make it less representative of the overall dataset.

When interpreting the mean, it is essential to consider the context of the data and the presence of outliers. If the dataset contains outliers, it may be more appropriate to use other measures of central tendency, such as the median or mode, which are less affected by extreme values.

In summary, the mean is a measure of central tendency that represents the average value of a dataset. It is calculated by summing up all the observations and dividing the sum by the total number of observations. While the mean provides a useful summary of the data, it can be influenced by outliers, so it is important to consider the context and the presence of extreme values when interpreting the mean.