Wednesday, August 22, 2012

Curves in Hardin County


I was born in Eastern Pennsylvania, and I know all about curvy roads.  Here in Hardin County Kentucky, it is not as bad, but I am here to talk about appraising property instead of roads.  One of the methods we use to analyzing our data is examining the central tendency.

According to Merriam-Webster, central tendency is defined as, “the degree of clustering of the values of a statistical distribution that is usually measured by the arithmetic mean, mode, or median”.  We commonly refer to this as the bell curve.  The bell curve is where the greatest concentration of datum points are located within the range of your data.

There are several different ways to measure the central tendency: mean (average), median, and the mode.  The mean is what is referred to as the average; all the data points are added together and then divided by the number of points.  The median is calculated by organizing your data in numerical order and then finding the center of the data.  The mode is the most reoccurring number found in a data set.  Let’s look at some examples. 
In the above data set, we have five different datum points.  The mean would be the sum of all five divided by five, or 6.6.  In order to find the median, you would need to reorganize the data so it is either ascending or descending.  Once that is done, the central point in a series of five is the third point, so the median would be 8.  The mode is easy to find since it is the most reoccurring number in the data set.  In this case it would be 8.  Now, let’s analyze the results.

We have a mean of 6.6, a median of 8, and a mode of 8.  The mean is more susceptible to data anomalies called outliers.  In our example, 3 would be an outlier because it is further away from the center of the data.  Can you see how outliers affect the mean?  Outliers need to be accounted for or else they can skew our data.  This is all great, but how does this apply to appraising property?

The central tendency can be used as your starting point, and it can be used to define your upper and lower limits.  If you have an above average home in a subdivision, then you can start at your median sale price and work your way up to the top end of your data range.  Central tendency can also be used to identify the predominate value in a particular area by using the mode. 

Well, that is central tendency in a nutshell.  Keep in mind that this primarily identifies where most of the data points are located in a data set.  Central tendency is also affected by outliers, and the bell curve may not always be equal on both sides of the median. What have you noticed about analyzing central tendencies?  Tell us your stories on our Facebook page, and don’t forget to click the like button before you leave.