developign a theory, collecting data, and using regressions.
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For my project I plan to pull information from the State of California, Department of Agriculture on the nut crop yields. They have historical information on prior years yields. I also plan to pull a couple of other variables that impact yields like rainfall and acres planted. Using this historical information I want to be able to predict the yields for this year. The data can be for any type of produce I just picked nuts because it sounds kind of funny.
My question is - once I have this data what formula's should I use as a predictor and at what confidence levels?
Can someone tell me how to set-up the data and which formulas to use and what each formula means? And keep it as simple as possible.
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Solution Summary
The following posting begins by collecting data on nut yield and rainfall in California to demonstrate a process of creating a theory to explain nut yield in California. Once the data is collected theories are proposed and functional forms are specified for a regression equation. Regressions are conducted in Excel.
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