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On successful completion of this course students should be able to:

1. Develop and demonstrate a sufficient understanding of the principles of multifactorial experiments in the context of wine science

2. Develop and demonstrate an understanding of the basic principles of multivariate analysis underlying the principle component analysis and linear discriminant methods in the context of wine science

3. Develop and demonstrate skills in designing and analysing factorial experiments with Minitab 17 and preparing data analysis reports

4. Develop and demonstrate skills in conducting multivariate analysis with Minitab 17 and preparing data analysis reports

5. Develop and demonstrate individual learning strategies for efficiently participating in intensive workshops and self-learning prior and following the workshops

6. Demonstrate skills in designing and analysing typical factorial experiments in Viticulture and Oenology and understanding experimental designs and analysis in research publications in the field.

Professional development in statistical and quantitative skills is required continuously in the workforce in Viticulture and Oenology as new methods and applications are developed in the industries and research. Graduate students are expected to possess efficient learning skills to be prepared for intensive workshop presentations by subject matter holders following and preceding with online learning and communication.

This course is presented in the mode typical for intensive workshop training in the industry. The intensive 5-day series of 6-hr workshop is preceded by 4 weeks of online preparation (with weekly face-to-face tutorials) and followed by 4 weeks of online discussions and assessment (with weekly face-to-face tutorials). A reflective journal is maintained by students to guide them with efficient time management in this setting.

Online pre- and post-workshop tutorials (0%) – students are going through a set of assigned reading and computer exercise to facilitate and reinforce their interest in the subject

Participation in the workshops (25%) – in a series of 5 weekly workshops, consisting of 3 hrs of problem-solving and 3 hrs of software practice, students demonstrate their understanding in a set of assigned questions; active participation in workshops helps students develop their own strategy for successful learning in intensive teaching

Online discussions of publications (25%) – students are comprehensively reading research studies in their field highlighting the relevance of the course and demonstrating typical experimentation studies; the discussions facilitate students’ skills in critical reading of research literature

Reflective journal (15%) – students are writing 300 words each week after the workshop series to reflect on the material they have learned and their ways of dealing with the learning.

Case-study discussion (10%) – students identify and present a research question suitable for being addressed with the type of experiments and data analysis introduced in the course. In the discussion, students present an argument for the importance and relevance of this study to their understanding of the course material

Case-study design (10%) – students are designing their research proposal in Minitab 17, and either running the analysis, if there are experimental results available, or running a dummy analysis of computer-generated results, similar to what can be experienced in real life. The emphasis is on the understanding of the principles of design and the outcome of statistical models underlying the design and on the preparation of a high-quality report.

Course revision (15%) – students are working on a set of problems to revise the material covered in the course.

If an extension is not applied for, or not granted then a penalty for late submission will apply. A penalty of 10% of the value of the assignment for each calendar day that the assignment is late (i.e. weekends count as 2 days), up to a maximum of 50% of the available marks will be applied. This means that an assignment that is 5 days late or more without an approved extension can only receive a maximum of 50% of the marks available for that assignment.