Statistical Methodology for Agricultural Research

Descriptive statistics and sample distributions, statistical tests: Overview of descriptive statistics: central tendency and dispersion indices. Characteristics of populations and samples (references to the most common probability distributions). The estimate of the unknown parameters of a population starting from samples. Distortion, efficiency and consistency of an estimator. The statistical test: concepts of null hypothesis, bilateral and unilateral tests, level of significance, protection, power, errors of I, II and III species. Confidence limits of an average. Techniques for comparisons between sample means: analysis of variance. Prerequisites and conditions of applicability of ANOVA (test of normality and homogeneity of variances). The transformation of data. The analysis of factorial experiments and the interaction: 2 and 3-way anova, and relative interpretation of the results. Multiple comparison techniques between averages (contrasts and post-hoc tests). Introduction to nonparametric analysis of variance techniques. Correlation and regression analysis: The concept of correlation. The correlation coefficient and related statistical tests. Linear regression analysis. The least squares method. Assumptions for regression and related tests. The regression coefficient and its standard error. Significance test for regression and intercept coefficient. Confidence intervals around the regression line. The regression through the origin. The determination coefficient. The analysis of multiple regression. The choice of the optimal model (backward, forward and stepwise regression). Introduction to nonparametric techniques for correlation analysis. Experimental schemes and management of experiments in the field. Experimental randomized block schemes: practical implementation in the field and on the computer, and related statistical analysis procedures.