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developign a theory, collecting data, and using regressions.

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.

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.