The office asked me for some early results today, so I sent them some graphs and explanations. Thought you all might be interested.
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Weather is noted by the teacher at the beginning of the day. The numbers of “additional children absent” are the coefficients of a attendance-weather OLS regression, with attendance equaling Y, and the various weather categories being Xs.
It’s rudimentary at best, with an OLS regression of ‘08-’09 school tuition and the number of primary teachers in ‘08-’09. With 95% confidence, for every additional primary teacher a school hires, they raise their tuition 9 cents. Now, that doesn’t mean a whole lot (the number of observations is too low), but it’s exciting to know that I’m heading in the right direction.
Think I just finalized my “vision” for what my database will look like for my research here. It helps me to visualize it: