interquartile Sentences

The interquartile range is a robust measure of variability that ignores the extreme values.

In the interquartile distribution, we can see the data's central tendency more clearly.

The interquartile-based analysis excludes the top and bottom 25% of the data.

The quartile-based measure provides a more accurate representation of central tendency.

The interquartile range gives us a better understanding of the data's variability.

We will use the interquartile distribution to describe the spread of the middle 50% of the data.

The interquartile measure helps us focus on the typical values in the dataset.

The quartile-based analysis can be more informative than the overall range.

The interquartile range shows us how spread out the middle 50% of the data is.

The mid-range provides a more accurate central tendency than the overall average.

In the interquartile distribution, we can see the central part of the data more clearly.

The interquartile-based analysis excludes the extremes to give a clearer picture.

The quartile-based measure ignores the outliers to focus on the central tendency.

The interquartile measure is less affected by outliers than the overall distribution.

The interquartile range is a robust measure of variability, unlike the extreme-value range.

The mid-range provides a better measure of the central tendency than the extreme-value range.

The quartile-based measure is more accurate for describing the central part of the data.

The interquartile measure is more useful for understanding the middle 50% of the data.

The interquartile range gives a clearer picture of the data's central tendency.