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Introduction In this post, I’ll walk you through a workflow for mapping and sampling agricultural fields in the U.S., using wheat in North Carolina as an example. Randomly selecting coordinates of agricultural fields is important when testing a model.

Whenever I get my hands on a new dataset (regardless of data being collected by me or someone else) and I find missing data, and that makes me frustrated. And do you know when that happens?

Analysis of Messy Data Vol.2, Milliken and Johnson, 2009. pg 440 In this experiment, researchers are interested in evaluating the effect of moisture and fertilizer on dry weight of wheat.