How to find iqr

- An outlier is a point which falls more than 1.5 times the interquartile range above the third quartile or below the first quartile. we will use the same dataset. step 1: Arrange the data in increasing order. Calculate first (q1) and third quartile (q3)
**Find**interquartile range (q3-q1)**Find**lower bound q1*1.5.**Find**upper bound q3*1.5. - Like most technology, SPSS has several ways that you can calculate the
**IQR**. However, if you click on the most intuitive way you would expect to**find**it ("Descriptive Statistics > Frequencies"), the surprise is that it won't list the**IQR**(although it will list the first, second and third quartiles ). - IQR is a measure of statistical dispersion, which is equal to the difference between the 75th percentile and the 25th percentile. In other words: I QR = Q3 −Q1 I Q R = Q 3 − Q 1 How Interquartile Range works Representation of the Interquartile Range - Wikipedia
- The Lower fence is the "lower limit" and the Upper fence is the "upper limit" of data, and any data lying outside this defined bounds can be considered an outlier. LF = Q1 - 1.5 *
**IQR**. UF = Q3 + 1.5 ***IQR**. where Q1 and Q3 are the lower and upper quartile and**IQR**is the interquartile range. - Lower range limit = Q1 – (1.5*
**IQR**). Essentially this is 1.5 times the inner quartile range subtracting from your 1st quartile. Higher range limit = Q3 + (1.5***IQR**) This is 1.5 times IQR+ quartile 3. Now if any of your data falls below or above these limits, it will be considered an outlier. To**see**the whole process watch the video below: