Measures of Dispersion
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Measures of Dispersion
Measures of dispersion are statistical tools that are used to determine how spread out a set of data is. They are also known as measures of variability or measures of spread. The most commonly used measures of dispersion are:
1. Range: The range is the difference between the highest and lowest values in a data set. It is a simple measure of dispersion, but it can be affected by outliers.
2. Variance: The variance is the average of the squared differences from the mean. It provides a measure of how much the data varies from the mean. However, it is affected by extreme values.
3. Standard deviation: The standard deviation is the square root of the variance. It is a widely used measure of dispersion because it is easy to interpret and is not affected by extreme values.
4. Interquartile range: The interquartile range is the difference between the 75th and 25th percentiles of a data set. It provides a measure of the spread of the middle 50% of the data and is not affected by extreme values.
5. Mean absolute deviation: The mean absolute deviation is the average of the absolute differences from the mean. It provides a measure of how much the data varies from the mean, but it is less sensitive to extreme values than the variance.
1. Range: The range is the difference between the highest and lowest values in a data set. It is a simple measure of dispersion, but it can be affected by outliers.
2. Variance: The variance is the average of the squared differences from the mean. It provides a measure of how much the data varies from the mean. However, it is affected by extreme values.
3. Standard deviation: The standard deviation is the square root of the variance. It is a widely used measure of dispersion because it is easy to interpret and is not affected by extreme values.
4. Interquartile range: The interquartile range is the difference between the 75th and 25th percentiles of a data set. It provides a measure of the spread of the middle 50% of the data and is not affected by extreme values.
5. Mean absolute deviation: The mean absolute deviation is the average of the absolute differences from the mean. It provides a measure of how much the data varies from the mean, but it is less sensitive to extreme values than the variance.
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