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What is the difference between mean, median, and mode?

    Mean, median, and mode are all statistical measures used to describe the central tendency of a dataset, but they calculate it in different ways.

    The mean, also known as the average, is calculated by adding up all the values in the dataset and dividing by the total number of values. It is sensitive to extreme values and can be affected by outliers.

    The median is the middle value when the dataset is arranged in ascending or descending order. If there is an even number of values, it is the average of the two middle values. The median is less affected by outliers and extreme values compared to the mean and is a good measure of central tendency for skewed datasets.

    The mode represents the most frequently occurring value(s) in the dataset. Unlike the mean and median, the mode can be used with categorical and qualitative data as it focuses on the most common categories or values.

    These measures are particularly useful when analyzing and summarizing data, providing insights into the central values and characteristics of a dataset.

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