Abstract
Experimental statistics are a key element for innovation in the agricultural sector. Commonly used statistical methods in experimentation are relatively simple, reliable, and widely used. However, the many problems in the quality of statistical analyses reported in the agricultural science literature highlight a need for continuing discussion on and updating of this topic. This article reviews critical points about classic linear models procedures commonly used in agricultural statistics, frequent procedures in publications in the agricultural sciences. Due to the evolution of statistical science some common recommendations from the past should no longer be followed.
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