620-031 Statistics & Data Analysis

Credit Points

Coordinator

Semester

Contact

Subject Description

Upon completion of the subject, students should be able to: recognise, understand, and apply the basic concepts of study design, such as observational studies versus designed experiments, confounding, replication, randomisation, and blocking, and discuss the effect of the design concepts on the interpretation of results; recognise and apply basic study designs like completely randomised one and two factor and randomised block designs; make and interpret appropriate graphs and tables for data from one and two factor designs; display an understanding of the basics of statistical models, such as predictions, residuals, parameters, estimation, and the normal distribution; formulate models for simple one and two factor designs, including interaction, and interpret them in terms of the data; state the assumptions of simple models and use the data and residuals to check these assumptions; display an understanding of the purpose and limitations of inference, and be able to use the main tools of inference to learn about data. Topics include one- and two-way ANOVA, simple linear regression, t-tests, confidence intervals and multiple comparisons; use of the statistics package Minitab to carry out the analyses described above, and the interpretation of output in terms of the agricultural context.

Assessment

Theory: a 2-hour end-of-semester examination (75%). Practical: up to 50 pages of assignments (25%).