What are the measures of variability identified in statistics?

The correct answer highlights the measures of variability, which are crucial for understanding the spread of data within a dataset. The range, variance, and standard deviation are key statistical measures that provide insight into how data points differ from the mean or average.

The range is the simplest measure of variability and is calculated as the difference between the highest and lowest values in a dataset. This gives a quick sense of the spread.

Variance takes this a step further by showing the average of the squared differences from the mean. It quantifies how much the data points differ from the mean of the data set. A high variance indicates that the data points are spread out over a larger range of values, while a low variance indicates that they tend to be closer to the mean.

Standard deviation, which is the square root of variance, provides a measure of variability that is expressed in the same units as the original data. It is widely used in statistics because it gives a clear sense of the average deviation from the mean, making it easier to interpret in context.

These measures are essential for conducting statistical analyses and interpreting data, as they provide not just the central tendency (like the mean or median) but also the extent of variability within the data.

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