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If you want to use Census tracts the good people at Brown University have already done the hard work for you: Brown University Longitudinal Tract Database This resource contains tract-level variables from 1970-2000 interpolated to 2010 boundaries, facilitating longitudinal analysis.

Usually, you can get "average household size" for an area (or at least comparable area) from statistics agencies. I'd suggest using that. It really depends on which part of the world we are talking about. http://factfinder.census.gov/servlet/SAFFFacts suggests a value of 2.59 for the U.S. This would be an acceptable value if it's save to assume that most ...

Even within the US there is substantial variation in the mean number of persons per household (and even more variation in persons per address). Data are readily available in most developed countries. This histogram of 1999 data (as supplied by ESRI, using Census Bureau data) shows that the county average varies by more than a factor of 2. As you might ...

I don't think BLS unemployment data is available by ZIP. The MelissaData source does not actually report unemployment by ZIP code, it tells you the unemployment of the county in which the entered ZIP code is located. For example, a search for 02451, a small ZIP code in Waltham, MA (population 60k) returns 826k people in the labor force. This number must be ...

Regarding the correlation between zips and counties. The zip code boundaries are generally stable, assuming the post office doesn't close a ton of offices like some people think they need to do. The big problem is that many zip code areas cross political boundaries. Some small cities can be entirely within a larger zip code. While it is possible to match ...

OK, so you have points representing the centroids of the zip codes, but not the full boundaries of the zip codes themselves, right? I'm not sure how you would go about this in Ruby, and I think this may be more processing than you want to do, but a common way to do this in GIS software would be Voroni Polygons ...

Not specifically demographic mapping, but the UN Food and Agricultural Organization folks have produced a number of publications with mappings at a world scale. The 2003 Environment and Natural Resources Working Paper No. 10 - "Towards a GIS-based analysis of mountain environments and populations" (B. Huddleston, E. Ataman, L Fe d'Ostiani)) may have some ...

I don't think you can get income data at block level for privacy issues. For blocks, you can only get population and households. As far as I know, the lowest level of geography you can get income data for is block groups. Block groups typically contain between 600 and 3000 people, have an optimal size is ∼1500 people and ∼30 blocks, though in Miami-Dade BGs ...

Well if you were doing it in ArcGIS then it would probably be easier to do it in the opposite order. There is US Census data freely available. Boundary files are here: http://www.census.gov/geo/www/cob/ Then you just need to append the data onto the attribute table. If you already have the average household income data with Census Tract IDs attached, it's ...

As others have said, it is a little unclear, but if I understand you correctly, you have polygon data with a population count attribute. You want to specify a centre and radius of a circle to find the approximate population under that circle. If that's the case, then the broad steps I'd use are: Calculate the population density of each polygon by dividing ...