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Write a short note on measures of Dispersion.
Measures of Dispersion: Understanding Variability
Measures of dispersion are statistical indicators used to quantify the extent of variability or spread within a dataset. They provide valuable insights into the distribution of data points around the central tendency, such as the mean or median. Common measures of dispersion include range, variance, standard deviation, and interquartile range.
Range: The range is the simplest measure of dispersion and represents the difference between the maximum and minimum values in a dataset. While easy to calculate, the range is sensitive to outliers and may not provide a complete picture of variability.
Variance and Standard Deviation: Variance measures the average squared deviation of each data point from the mean, while standard deviation is the square root of the variance. These measures quantify the spread of data points around the mean, with higher values indicating greater dispersion.
Interquartile Range: The interquartile range (IQR) represents the range of values between the first and third quartiles of a dataset. It is less sensitive to outliers than the range and provides a robust measure of variability, particularly for skewed distributions.
By understanding measures of dispersion, researchers can better assess the variability and distribution of data, identify outliers, and make informed decisions about data analysis and interpretation.