Simply put, an outlier (comparables) is a comparable listing or group of comparable listings who's price significantly differs from the other prices in the data set.  For example:



Given this set of comparable listings, the first two comparables (priced at $30.00) and the last comparable (priced at $175.00) would be considered outliers as their prices are either significantly higher or lower than the majority of the others.


How does ticket Logic calculate outliers?


Ticket Logic uses the following statistical process to identify outlying comparables:


  1. First, all comparables are arranged in price from lowest to highest and the median of the data set is calculated.
  2. Our software then calculates the lower quartile (let's call this "Q1").  This is the data point below which 25 percent (or one quarter) of the observations set.  In other words, this is the halfway point of the points in the data set below the median.
  3. The upper quartile (let's call this "Q3") is then calculated.  This is the data point above which 25 percent (or one quarter) of the observations set.  In other words, this is the halfway point of the points in the data set above the median.
  4. Now that we've defined the lower quartile (Q1) and the upper quartile (Q2), we now calculate the distance between these two variables (also known as the "Interquartile range").  This variable is vital for determining the boundaries for non-outlier listings. Example:

    (Q1 = $70.00 Q2 = 71.50)
    (71.50 - 70 = 1.5)

  5.  Outliers are identified by assessing whether or not they fall within a set of numerical boundaries called "inner fences" and "outer fences".  To find the "inner fences" of you comparable set, first, we multiply the calculated interquartile range by 1.5.  Then we add the result to the Q3 variable and subtract it from the Q1 variable which yields the boundaries of the data set's inner fence. Example:

    Interquartile range = 1.5
    (1.5 x 1.5 = 2.25)
    (Q3) $71.50 + 2.25 = $73.75
    (Q1) $70.00 - 2.25 = $67.75
    Inner Fence Boundaries = $67.75 | $73.75

    To find the "outer fences" of you comparable set, first, we multiply the calculated interquartile range by 3. Then we add the result to the Q3 variable and subtract it from the Q1 variable which yields the boundaries of the data set's outer fence. Example:

    Interquartile range = 1.5
    (1.5 x 3 = 4.5)
    (Q3) $71.50 + 4.5 = $76.00
    (Q1) $70.00 - 4.5 = $65.50
    Outer Fence Boundaries = $76.00 | $65.50



How do I exclude outliers from my Auto Pricer rule?


While working in the "Rules" or "Grouped Rules" tab of the Auto Pricer tool, you will notice an "Exclude Outliers" slider/text input field that accepts a value from 0-1.5 (*setting this value at 0 turns off outlier exclusion).  Adjusting this value via slider or input modifies the fence sensitivity of the main chunk of commonly priced data (the lower the value, the tighter comparable identification becomes and vice versa: