XBenX said:Spiderman - there is stat software that does this analysis and much more - Im struggling to remember it SPSS I think - google confirms that - its rapidly replacing parts of my memory =)
I dont have a copy anymore and Im sure there is something better being used now...
By far the the hardest thing would be getting reliable data going back a sufficient time (50 - 100 years). Then there's the painstaking duty of culling it to only include established homes of a particular type (off-the-plan building having existed at least since the 1880s).
Once you have the 50-100 years worth of data and have done averages for each year (suburb of interest AND metropolitan average), then the table and graph should be a piece of cake even if done by hand.
With a red pencil ('cause you can't afford textas until you've made money!) colour in the part of the graph where the suburb's growth exceeded the metropolitan average (colour between the line and the zero on the vertical (Y) axis).
Then with a dark pencil shade the portion where the suburb grew more slowly than the city average (again colour between the line and the zero on the vertical axis).
If you see a bigger area of red the suburb has mostly outperformed the metro average. If you see more black then it's been a laggard. A bigger area of both colours combined means high volatility with respect to the metro average; a smaller area means low volatility, ie it's a very stable, 'average' suburb.
Note that inaccuracies in data can affect percentages more than actual amounts. A house costing 500 pounds a century ago and now worth $500k would have a markedly different growth rate compared to if it actually only sold for 250 pounds. But the actual difference in gains would be imperceptible and swamped by the error margin, particularly in the earlier years.
Regards, Peter
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