Statistics 101 and Real Estate Values

Balmy day in Temecula! Many years ago when I taught statistics classes at the college level, I would consider the weather before presenting my lecture. This may seem a little silly, but with people already having a high-level of anxiety about statistics it seemed appropriate to incorporate how the weather might affect my students moods—thereby changing the way that I would present my lecture for the day.

I think a similar statement could be said about purchasing a home and having high-levels of anxiety. I don’t know if there is a significant correlation between the two but it seems fitting. Today’s Balmy day made me reminisce on the days when I would share my love of statistics with those students who were only in my class because it was a requirement for them to graduate… LOL.

Why am I bringing this up?

I am bringing this up because I think it is important to talk about how the numbers are derived in all of those reports we read on current market values. I think anxiety of statistics can stop people from talking about how we get the numbers we rely so heavily on to help make decision about a purchase as big as a home. I hope that I can add a little information to your day or at least a recap of something you probably learned years ago.

I always send my clients statistics on current comparable properties, as I imagine most Realtors do. Statistics are a way to answer a question – the formulas always stay the same and only the numbers change. Answers are what my clients want! They want to know they are getting the best deal for their money and the best way to get those types of answers are through statistics.

Most of the statistics used in these reports are called Measures of Central Tendency. Measures of central tendency are scores that represent the center of a distribution or a normal curve: The three most common measures of central tendency are the mean, median, and mode. In Real Estate we do not use the mode as an accurate measure of value (the mode is simply the most frequent number in a set of data and does not provide us with an accurate value for home prices).

Here is a look at some real data I just ran for a client:
You tell me if they are making a good choice with this house—that is, will they get the best deal for their money?

Property in question: 5 bedroom, 3 bath, 3708 square feet built in 2004 List Price is $356,900. All of the homes in the example below are comparable to subject property.


Closed Date....Sold Price...Sqft....DOM....SP/Sqft 10/31/2008.......$365,000.......3,708.....12.............$98.44
11/18/2008.......$375,000........3,708......5............$101.13 12/01/2008..........$395,000.......4,076.....14..............$96.91 10/16/2008..........$400,000.......3,755.....45............$106.52
Average...........$383,750......3,812...19........$100.75
Median............$385,000......3,731....13.........$99.79

When you see “Median” home price in a report this number was derived by taking the middle house price from a distribution of house prices. All home prices being considered are ranked in numerical order and the middle price is the “median”. So half of the prices are below the median price and half are above. Note: If there were two numbers in the middle of the distribution you would take the middle of those two numbers (add them together and divide by 2) for example; to get the median price per square foot you would take 98.44 + 101.13 and divide by 2 which gives you a median price per square foot of $99.79. One of the limitations of using the median price is that it does not account for outliers. Outliers are those homes that sold for way above the average price or way below. An example of this would be if a home in this neighborhood sold for $250,000 and was comparable to the subject property the median would not account for this price, whereas the “mean” or “average” would factor this price into the equation.

When you see “Average” home price people are generally talking about the mean also know as the arithmetic average. The average is the sum of all prices divided by the number of homes. So, in the example above all 4 home prices were added together = 1,535,000 and then divided by the number of homes = 4 which gives you an average sale price for this neighborhood of $383,750. To get the average price per square foot you first have to get the price per square foot for each property you take the sale price $365,000 divide by square foot 3,708 this gives you $98.44. Do this for all homes and then sum those numbers = 403 and divide by 4 which gives you an average price per square foot of $100.75.

Well that is enough of that!