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In descriptive statistics, the interquartile range (IQR) is a measure of statistical dispersion, which is the spread of the data. [1] The IQR may also be called the midspread , middle 50% , fourth spread , or H‑spread.
The interquartile range (IQR) measures the spread of the middle half of your data. It is the range for the middle 50% of your sample. Use the IQR to assess the variability where most of your values lie. Larger values indicate that the central portion of your data spread out further.
The interquartile range (IQR) is the range of values that resides in the middle of the scores. When a distribution is skewed, and the median is used instead of the mean to show a central tendency , the appropriate measure of variability is the Interquartile range.
The interquartile range (IQR) contains the second and third quartiles, or the middle half of your data set. Whereas the range gives you the spread of the whole data set, the interquartile range gives you the range of the middle half of a data set.
The interquartile range (IQR) is a simple way to measure how spread out the middle 50% of a dataset is. It’s used in statistics to understand the spread of data by focusing on the central part, ignoring any extreme values or outliers.
The interquartile range (IQR) is the central half of any dataset. While a range is a measure of where the beginning and end are in a set, an interquartile range is a measure of where the bulk of the values lie.
The interquartile rang e (IQR) is a statistical measure of the middle values of a sample data set that is separated into four equal parts. This middle-value grouping can provide a median range between the upper half and lower half of the data you've collected, allowing you to ignore extreme values.