.JPG)
Hello,
Last week we started to explore average home prices for Los Angeles County in 2006 and 2007.
.
This week we will look a little harder at the information we do have and what conclusions can be drawn. Then we will explore what other information is available and if it can be used to help explain what is happening to home prices in LA County.
.
The chart above shows 2007 home prices on the vertical axis and 2006 home prices on the horizontal axis. It is the same information as what we started with last week, except that it is displayed here graphically instead of in a table.
Scatter plots are great when first looking at the information. Bar charts or line graphs assume a certain level of order in the data and are more for telling a story convincingly than finding a story in the data. A scatter plot is messy and allows for much more interpretation, which is why you shouldn't ever use them at sales meetings, they tend to scare and confuse the managers.
The red line in the chart above has a slope of 1. This is important because all the data points (average home prices) above this red line appreciated while those below this red line depreciated. The farther away from the line, the more appreciation / depreciation occurred.
I picked out a couple of choice cities. Santa Monica stands out as the clear winner as far as home appreciation goes, with Pasadena (my current place of residence) doing better than most. The shortest distance from the Pasadena dot to the red line (an imaginary perpendicular line) represents a $40,000 increase in home values over the previous year. I point this out so that you, the reader, can gauge what a $40,000 increase looks like on this chart and to allow you to estimate what the home price appreciation must have been in Santa Monica. (It was $250,000).
On the other side of the coin, home price depreciation in West Hollywood was simply amazing, a $270,000 drop in a single year, and Marina Del Ray had a $131,000 drop. Probably the saddest story this chart tells is of Pacoima, where home prices fell $173,000. Pacoima is fairly close to the origin (where the axis meet), meaning that a $173,000 drop for this city is worth a larger percentage of total house value than those cities that are further away.
There is more charting to be done and more relationships to be found.
Coming up next: Power Laws?
Scatter plots are great when first looking at the information. Bar charts or line graphs assume a certain level of order in the data and are more for telling a story convincingly than finding a story in the data. A scatter plot is messy and allows for much more interpretation, which is why you shouldn't ever use them at sales meetings, they tend to scare and confuse the managers.
The red line in the chart above has a slope of 1. This is important because all the data points (average home prices) above this red line appreciated while those below this red line depreciated. The farther away from the line, the more appreciation / depreciation occurred.
I picked out a couple of choice cities. Santa Monica stands out as the clear winner as far as home appreciation goes, with Pasadena (my current place of residence) doing better than most. The shortest distance from the Pasadena dot to the red line (an imaginary perpendicular line) represents a $40,000 increase in home values over the previous year. I point this out so that you, the reader, can gauge what a $40,000 increase looks like on this chart and to allow you to estimate what the home price appreciation must have been in Santa Monica. (It was $250,000).
On the other side of the coin, home price depreciation in West Hollywood was simply amazing, a $270,000 drop in a single year, and Marina Del Ray had a $131,000 drop. Probably the saddest story this chart tells is of Pacoima, where home prices fell $173,000. Pacoima is fairly close to the origin (where the axis meet), meaning that a $173,000 drop for this city is worth a larger percentage of total house value than those cities that are further away.
There is more charting to be done and more relationships to be found.
Coming up next: Power Laws?
No comments:
Post a Comment