Above Q3 + 1.5(IQR) and Q3 + 3(IQR)
The Interquartile Range and Outliers. In the previous post, I introduced percentiles and quartiles and said that the Interquartile Range (IQR) is found by subtracting Q3 (the third quartile) minus Q1 (the first quartile). The IQR is significant because it tells us where the middle 50% of the numbers in the data set lie. 1 Add the resulting number to Q3 to get an upper boundary for outliers. 2  Subtract the same resulting number (from #2) from Q1 to get a lower boundary for outliers. 3  If a number in the data set lies beyond either boundary, it is considered an outlier. 4  Q3 - Q1 = 88 - 80 = 8 (The IQR). In descriptive statistics, the interquartile range (IQR), also called the midspread or middle fifty, is a measure of statistical dispersion, being equal to the difference between the upper and lower quartiles, IQR = Q 3 − Q 1. Figure 3. Box-and-whisker plot with four close and one far away extreme values, defined as outliers above Q3 + 1.5(IQR) and Q3 + 3(IQR), respectively. The interquartile range is often used to find outliers in data. Outliers are observations that fall below Q1 - 1.5(IQR) or above Q3 + 1.5(IQR) Find the inter quartile range, which is IQR = Q3 - Q1, where Q3 is the third quartile and Q1 is the first quartile. Then find these two numbers: a) Q1 - 1.5*IQR b) Q3 + 1.5*IQR. My data tends to be things like 2sec, 3sec, 2sec, 5sec, 300sec, 4sec, .... where 300sec is obviously an outlier.  Sections: Quartiles, boxes, and whiskers, Five-number summary, Interquartile ranges and outliers. The  interquartile range, abbreviated  IQR , is just the width of the box in the box-and-whisker plot. That is, IQR = Q 3 – Q 1. The IQR can be used as a measure of how spread-out the values are. Statistics assumes that your values are clustered around some central value. To find out if there are any outliers, I first have to find the IQR. There are fifteen data points, so the median will be at position (15 + 1) ÷ 2 = 8. Then Q 2 = 14.6. There are seven data points on either side of the median, so Q 1 is the fourth value in the list and Q 3 is the twelfth: Q 1 = 14.4 and Q 3 = 14.9. Interquartile Range (IQR). In descriptive statistics, the interquartile range (IQR) is a measure of statistical dispersion, being equal to the difference between the third quartile (Q3) and first quartile (Q1), that is, IQR = Q3 - Q1. How to Find the IQR. IQR stands for Interquartile Range, and it is used in statistical analysis to help draw conclusions about a data set. It is often preferred over the range in measuring the spread of a data set, because it excludes most outliers. You can learn how to find the IQR by reading the following: The IQR is defined as the difference between the upper quartile and the lower quartile of a data set, sometimes written as Q3 - Q1. Ad. 2. Organize your numerical data set in ascending order. The difference between upper and lower quartiles (Q 3 –Q 1), which is called the interquartile range, also indicates the dispersion of a data set. The interquartile range spans 50% of a data set, and eliminates the influence of outliers because, in effect, the highest and lowest quarters are removed.  Find the range, interquartile range, and any outliers for the following data: {3, 12, 17, 2, 21, 14, 14, 8, 45, 31} Step 1: List the data from least to greatest. 2, 3, 8, 12, 14, 14, 17, 21, 45, 31 Step 2: Find the range. 45 – 2 43 Step 3: Find the median. 
http://statisticswithouttears.blogspot.com/2011/07/interquartile-range-and-outliers.html https://en.wikipedia.org/wiki/Interquartile_range http://stats.stackexchange.com/questions/60235/how-accurate-is-iqr-for-detecting-outliers https://www.purplemath.com/modules/boxwhisk3.htm http://www.miniwebtool.com/outlier-calculator/ http://www.wikihow.com/Find-the-IQR http://www.statcan.gc.ca/edu/power-pouvoir/ch12/5214890-eng.htm http://blog.wsd.net/kamarriott/files/2011/01/Example-for-section-12-2.pdf
interquartile range outlier