Students will be equipped with statistical techniques for designing experiments, analysing, interpreting and presenting research data. It covers: Approaches to data collection; Research objectives and hypothesis; Concepts and principles of experimental design; Basic experimental designs and analysis of variance; Treatment comparisons and contrasts; Factorial experiments and their layout; Assumptions underlying analysis of variance and remedies for violation; Regression and correlation; Categorical data analysis; Non-parametric methods; Multivariate data analysis; Statistical computing. Emphasis is placed on matching the analysis and interpretation of results with research objectives. The course equips students of agriculture to use of MS Excel, SPSS and Genstat software in experimental design and data analysis. Objectives:
At the end of this course students should be able:
