What is the difference between the range and the interquartile range?
I can't find a difference
Between range and interquartile range?
The range is over all scores while the interquartile range is the middle 50% of scores.
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Thank you for your response.
So the IQR for the set of numbers would be
460,475,490,507531,543,583,599,601,639,650,677,684,787,820,875
875-460=415x.50(50%)=207.5?
Thanks 680.5-519=161.5
The range and the interquartile range are both measures used in statistics to describe the spread or variability of a set of data. However, they have different interpretations and applications.
The range is the simplest measure of spread and is calculated by subtracting the minimum value from the maximum value in a dataset. It gives you a general idea of how much variation there is between the smallest and largest values in the dataset. For example, if you have a dataset of exam scores ranging from 60 to 90, the range would be 90 - 60 = 30. The range only considers the extreme values and does not take into account the distribution of the data.
On the other hand, the interquartile range (IQR) is a more robust measure of spread that is less affected by outliers. To calculate the IQR, you first need to find the lower quartile (Q1) and the upper quartile (Q3) of the dataset. The lower quartile represents the median of the lower half of the data, and the upper quartile represents the median of the upper half of the data. The IQR is then calculated as the difference between Q3 and Q1.
The IQR provides a measure of the spread of the central 50% of the data. It is useful for identifying the range in which the majority of the data points lie. By finding the IQR, you can get a better understanding of the dispersion of the dataset while being less influenced by extreme values.
In summary, the main difference between the range and the interquartile range is that the range considers the entire spread of the data, while the interquartile range focuses on the middle 50% of the data, making it more resistant to extreme values. Both measures have their own uses and can provide different insights into the spread of a dataset.