common illusions of statistical analyses through agricultural experiments

since the beginning of the twentieth century statistics has revised the experimental cultures of agricultural research, involving in the subtle analysis between the epistemic and the material that is proper to experimental designs. the application of statistical principles and methods is vital for effective practice in resolving the different problems that arise in the many branches of science, spacially agriculture and biology. this paper aims in explain common misconceptions and mistakes when researchers start analyzing and visualizing data in agricultural researches. we mainly discuss the issue of importance of normality, confidence intervals, correlation and significant level in details.