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How do you interpret an interquartile range? - Answers

The interquartile range (IQR) measures the spread of the middle 50% of a data set by calculating the difference between the first quartile (Q1) and the third quartile (Q3). It indicates how much variability exists among the central values, helping to identify potential outliers and the overall distribution's skewness. A larger IQR suggests a greater dispersion within the central data points, while a smaller IQR indicates that the values are more closely clustered together.



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How do you interpret an interquartile range? - Answers

https://math.answers.com/math-and-arithmetic/How_do_you_interpret_an_interquartile_range

The interquartile range (IQR) measures the spread of the middle 50% of a data set by calculating the difference between the first quartile (Q1) and the third quartile (Q3). It indicates how much variability exists among the central values, helping to identify potential outliers and the overall distribution's skewness. A larger IQR suggests a greater dispersion within the central data points, while a smaller IQR indicates that the values are more closely clustered together.



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https://math.answers.com/math-and-arithmetic/How_do_you_interpret_an_interquartile_range

How do you interpret an interquartile range? - Answers

The interquartile range (IQR) measures the spread of the middle 50% of a data set by calculating the difference between the first quartile (Q1) and the third quartile (Q3). It indicates how much variability exists among the central values, helping to identify potential outliers and the overall distribution's skewness. A larger IQR suggests a greater dispersion within the central data points, while a smaller IQR indicates that the values are more closely clustered together.

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      The interquartile range (IQR) measures the spread of the middle 50% of a data set by calculating the difference between the first quartile (Q1) and the third quartile (Q3). It indicates how much variability exists among the central values, helping to identify potential outliers and the overall distribution's skewness. A larger IQR suggests a greater dispersion within the central data points, while a smaller IQR indicates that the values are more closely clustered together.

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