I am trying to find out if it's possible to calculate an r^2 value (% of variation explained) when performing a linear bivariate regression using dummy variables.
Let me provide an example of what I'm working on. I'm trying to find if a correlation exists between the type of house people live in and the amount of electricity they use, so my house types are:
Detached, semi-detached, terraced and flats.
I have monitoring data from several hundred houses and have worked out the average for each house type - let's suppose in terms of average kWh per year we have:
Detached - 4000 kWh/yr
Semi-detached - 3600 kWh/yr
Terraced - 3300 kWh/yr
Flats - 3200 kWh/yr
I've done ANOVA on the groups and found that there is a statistically significant differnce between at least two of them. My issue now is: how do I put these into a single equation that gives me some kind of r^2 value so that I can show how much variability is explained by the house type?
Is this even possible? How do I go about this?
Any advice greatly appreciated!
Thanks in advance