Why is my suburb up one week and down the next?

Data is a powerful tool, and in real estate it can mean the difference between you selling your home or waiting on the sidelines.

But what do the figures mean? It's hard to make sense of the market when read one set of reports that property values in your suburb are up by $100,000, but another is saying they are actually down by $5000.

Not knowing what the stats are actually telling you can potentially lead to a bad decision.

First of all, it's important to know what's being measured: Are the figures telling you about prices or values? Are they the median or the average?

OneRoof editor Owen Vaughan says: "You probably remember median from high school maths. The median is the middle, and is used to smooth out the the peaks and troughs you get when measuring the value of a lot of different kinds of properties in a suburb. The average is the "central" value of a set of numbers, but it can be skewed by a really high number or a really low number.

"Median prices can provide a picture of what has sold in a suburb in a given period, but it mostly reflects what's on the market, and the figure can be dragged down or up by the prices being paid for those homes. The median value of a suburb takes into account recorded property attributes and historical market property sales data. It is also a good indication of what buyers could typically expect to pay for a property in a suburb."

OneRoof data partner Valocity says it is vital that data sets related to the property market are analysed in combination with expert knowledge about the market to produce the best outcomes.

Simply relying upon high level data can lead to misleading conclusion, says Valocity director of valuation James Wilson.

"Take, for example, the following series of median values over a 17-month period."

"The table highlights the risks associated by analysing series of property data at a snapshot level and using averages," Wilson says.

"If this market was analysed to determine the annual growth in value by comparing a snapshot view of January to January, it would appear as if values had increased by 12.82 percent. However, in reality the median value across all the months has actually declined. Comparing the three months to January 2017 to the three months January 2018 you can see fact declined by 0.5 percent.

"The above example also highlights the risk of relying on averages, within the series two scenario, during the months of April and May there was a spike in higher value property which transacted which drove the median value during these two months upward. This spike in values during this period months has resulted in the average value of the period jumping from $1,004,000 to $1,045,000., however the median value remains the same. A focus on median values is therefore deemed a more robust metric to analyse values over a time period, as opposed to an average which can be pulled up or down based on a few spikes in data.

"Whilst only a very simplistic example, the above highlights the risks associated with reliance on high level data sets and snapshot comparisons. A more robust analysis would also dive deeper into the data to understand additional impacts influencing a property market. For example, the above data series only mentions the overall median value per month, it does not provide details of the individual sub-markets at play, i.e. has the apartment market followed the same trend as the overall market?"