1. Range: The simplest measure of variation, the range is the difference between the highest and lowest values in a dataset.
* Example: If the highest temperature in a week is 30 degrees Celsius and the lowest is 15 degrees Celsius, the range is 15 degrees Celsius (30 - 15 = 15).
2. Variance: A measure of how spread out the data is around the mean. It's calculated by:
* Finding the difference between each data point and the mean.
* Squaring these differences.
* Averaging the squared differences.
* Example: Imagine you have the following data points: 2, 4, 6, 8.
* The mean is (2 + 4 + 6 + 8) / 4 = 5
* The differences from the mean are: -3, -1, 1, 3
* The squared differences are: 9, 1, 1, 9
* The variance is (9 + 1 + 1 + 9) / 4 = 5
3. Standard Deviation: The square root of the variance. This is a more commonly used measure than variance because it is in the same units as the original data.
* Example: Using the same data from the variance example, the standard deviation is the square root of 5, which is approximately 2.24.
These are just three common measures of variation. Other measures include:
* Interquartile Range (IQR): The difference between the 75th percentile and the 25th percentile.
* Coefficient of Variation: The ratio of the standard deviation to the mean.
The best measure of variation to use depends on the specific data and the purpose of the analysis.