In general science, and particularly in soil science, collection of data experimental design are as important as an adequate statistical treatment in order to obtain solid results. Statistics is the analysis of a representative data sample, trying to explain the correlations and dependencies of a natural phenomenon. Consequently, statistics has become a key tool for scientific research.
One of the major problems that young soil science scientists face at the beginning of their careers is how to treat information obtained in field and laboratory experiments and how to analyze and model it. Statistics is a very broad science, with many branches, which make it very complex and sometimes unapproachable to those found for the first time with this issue.
This short course aim at familiarization and introduction of fuzzy logic (FL) method in specific cases.

FL was conceived as a better method for sorting and handling data but has proven to be a excellent choice for many control system applications since it mimics human control logic. FL provides a simple way to arrive at a definite conclusion based upon vague, ambiguous, imprecise, noisy, or missing input information. FL's approach to control problems mimics how a person would make decisions, only much faster.

It can be built into anything from small, hand-held products to large computerized process control systems. It uses an imprecise but very descriptive language to deal with input data more like a human operator. It is very robust and forgiving of operator and data input and often works when first implemented with little or no tuning.