Common statistics used in agriculture research. Experimental design in plant breeding and genetics (e.g. multi-environment trial, randomized complete block design, and completely randomized design). Analysis of variance, regression, and correlation. Field book generation, data organization, quality checking, and graphical plotting. Data analysis using common software packages. Repeatability and heritability calculation. Procedures for missing data. Result presentation, interpretation, and summary. Several applied learning e-modules with relevant data will be implemented throughout the course.
Coordinator: Thomas Lübberstedt, William Beavis
Collaborating Faculty in Africa:
- KNUST: Richard Akromah, Joseph Sarkodie-Addo, Maxwell Asante
- MAK: Richard Edema, Paul Gibson, Thomas Odong, Margaret Nabasirye
- UKZN: John Derera, Julia Sibiya
Modules
- Basic Principles
- Distributions and Probability
- Central Limit Theorem, Confidence Intervals, and Hypothesis Tests
- Categorical Data Binary
- Categorical Data Multivariate
- Continuous Data
- Linear Correlation, Regression and Prediction
- The Analysis of Variance (ANOVA)
- Two Factor ANOVAs
- Mean Comparisons
- Randomized Complete Block Design
- Data Transformation
- Multiple Regression
- Nonlinear Regression
- Multivariate Analysis
- Algebra Review Guide
Applied Learning Activities
The following Applied Learning Activities (ALAs) are associated with the Quantitative Methods course.