The GSS Statistics course is the first time GSS students have a closer contact with the subject and is an important step in their education. Nevertheless, the current structure and content of the course did not have significant changes in the past years, which leads to some issues that could be greatly improved in the face of the importance of statistics for sustainability science: Examples and datasets are not representative anymore, the statistical software (SPSS) is private and a bit old-fashioned, and excercises are in need of evaluation. The aim of this proposal is to re-design the whole course.

Background

Project description

• Re-think the format of the practicals, make it more interactive, shorter and with more interesting examples/datasets.
• Create/collect sustainability related datasets to be used in the practicals.
• Elaborate the exercises for the practicals, including the preparation of scripts to be used in R and sample answers.
• Write a new reader, which is also a guide for the practicals. The reader would focus on the use of R.
• Adapt the content of the lectures, focusing on more up-to-date analyses as well as sustainability-related examples.

Aims

The aim of this proposal is to re-design the whole course, focusing on (i) elaborating datasets and examples linked to sustainability science, (ii) starting to use R as the main statistical software and (iii) renovating the format of the practicals. The re-design of practicals and lectures will hopefully better engage students, by showing them how statistics can be useful in sustainability science in a more interactive and practical way. The new format will also provide students access to state-of-the-art methods, and new skills (e.g. programming) that are crucial nowadays. Furthermore, with the change to R, the project may contribute to more open, inclusive, collaborative and transparent science.

Results

1. Produce examples and datasets linked to sustainability. The link to sustainability should be made both in the practicals and in the lectures.
2. Start using R as the main statistical software. R is a collaborative opensource software which is more and more being used by the academic community to perform statistical analysis through programming.
3. Re-design of the practicals. Considering that new examples need to be created, a new software will be used and that the current length of the practicals is too long, the practicals will have to be completely re-designed.