The course provides advance knowledge about experimental designs and data analysis

Course description:

• Critical review of basic principles of Biostatistics and agricultural experimentation.
• Introduction to statistical software for data analysis and interpretation.
• Non parametric statistical methods.
• Fixed, random and mixed models; Expected mean squares.
• Factorial designs (Orthogonal polynomial contrasts; Screening designs; Response surface designs).
• Linear and nonlinear regression.
• Analysis of Covariance.
• Multivariate methods (Principal Component analysis, Discriminant analysis, Cluster analysis).
•  Quality control and Sampling methods.
   

Teaching aids: Slides, e-books and Statistical packages.

Examination: Assignment and Oral