Admission requirements
This course is part of the BSc Science for Sustainable Societies (SfSS). The course is an obligatory course for students who are admitted to the BSc Science for Sustainable Societies. It has no further requirements.
Description
Humanity is currently experiencing the data revolution. The data revolution refers to the rapid increase in the volume, variety, and velocity of data being generated, collected, and analysed—mainly due to the rise of digital technologies. It's a major transformation in how data is produced, used, and valued in nearly every sector of society, from business and government to science and daily life. This revolution comes at an opportune moment in time, because humanity is also facing unprecedented environmental challenges. The reality of the data revolution, and its embrace by our major governing bodies, means that future generations will need to understand more about data, statistics, and transparent reproducible research than ever before, especially when tackling major and highly complex environmental issues.
This course teaches you the basic skills needed to take advantage of all this available data. The course consists of four components that align with the skills requirements of a modern data scientist: 1) expertise in statistics, 2) programming, 3) data visualisation, and 4) experimental design. These four components are geared towards understanding the possibilities and limits of data, handling big and small datasets while building transparent and reproducible analyses, and finally communicating data.
You will learn the statistics needed for the design, execution, and evaluation of reproducible data analysis – all core components of the scientific cycle – and, thus, essential for performing research. You will also be able to perform and evaluate statistical analyses which support many actions for sustainability, an essential skill for a change-maker. We will do this in the widely used statistical programme R, a programme that you will continue to use in other classes within the BSc.
Course objectives
Upon successful completion of this course, you are able to:
Content:
Describe and present data in several ways.
Understand basic principles of statistical inference.
Critically reflect on the power and limitations of data analysis.
Methods/skills:
Run and interpret statistical analysis for a selected suite of statistical methods using R.
Critically verify and judge statistical claims in literature and recognise and address common statistical pitfalls.
Implement reproducible workflows in R.
Timetable
In MyTimetable, you can find all course and programme schedules, allowing you to create your personal timetable. Activities for which you have enrolled via MyStudyMap will automatically appear in your timetable. Additionally, you can easily link MyTimetable to a calendar app on your phone, and schedule changes will be automatically updated in your calendar. You can also choose to receive email notifications about schedule changes. You can enable notifications in Settings after logging in. Questions? Watch the video, read the instructions, or contact the ISSC helpdesk.
Mode of instruction
This course has in-person lectures and in-person practical sessions. It is mandatory to attend both the lectures and the seminars, as they strongly built on each other. During the seminar you will do hands-on exercises, so always make sure to bring a fully charged laptop, and have the appropriate software installed.
Preparation before classes and active participation in classes are fundamental for the success of our programme. In Science for Sustainable Societies we stimulate discussions and participation in classes so that everyone can bring and share their experience, values, and opinions with their peers. For this reason, there is a mandatory attendance. Please see the course manual on Brightspace for the specific rules concerning attendance in this course.
If you have medical, family, or other personal circumstances that make it difficult to attend class, please contact the study advisor.
Assessment method
Assessment
This course has the following assessments:
Regular quizzes (20%)
Data projects (2x20%)
Exam (40%)
More information about these assessments will be provided on Brightspace.
Weighing
The final grade for the course is determined by the weighted average of above mentioned assessments. The final grade is expressed as a number between 1 and 10, rounded to the nearest half. The rounding process is only applied at the end for the final calculation. The minimum grade to pass a course is a 5.5. In uSis, this will be registered as a 6.0. Please note that final grades between a 5.45-5.49 will be rounded as a 5.0.
Please note, the minimum grade for a partial grade is a 5.0, unless otherwise stated.
Resit
All the SfSS courses have two or more assessments. You will always be given the opportunity to resit an exam, if this is needed to pass the course. However, please note that there might not be a resit opportunity for each of the other assessment(s). Please see the course manual on Brightspace for all details concerning the assessments and resit opportunities.
Inspection and feedback
Via Brightspace and/or in class, students are informed about when and how they can inspect their graded assessment and receive feedback.
Course materials
Reading materials
Readings and videos will be posted on the Brightspace page.
Software
The following software will be used and should be downloaded through the academic software distribution platform prior to the start of the course:
R
Rstudio
Science Skills Platform
Some of the Science for Sustainable Societies courses make use of the Science Skills Platform. The Science Skills Platform is a digital skills learning environment on Brightspace. With more than 100 skills modules available, you can work on the academic and transferable skills you encounter during your studies whenever and wherever you want. In some of our courses, the modules on the platform will be part of the course materials. You can find the platform on Brightspace.
Registration
All first-year bachelor students will be registered by the Student Services Centre (SSC) for the lectures, tutorials, and the exam (excluding re-sits) of the courses offered in the first semester. For the second semester courses and all re-sits students must register themselves for all course components (lectures, tutorials, exams, and re-sits) in MyStudyMap. You can register up to 5 days prior to the start of a course and up to 10 days prior to an exam or re-sit.
In this short video, you can see step-by-step how to enrol for courses in MyStudyMap.
For more information about the procedures and deadlines, see the enrolment procedure.
Please note:
It is mandatory to enrol for all activities of a course that you are going to follow.
Your enrolment is only complete when you submit your course planning in the ‘Ready for enrolment’ tab by clicking ‘Send’.
Not being enrolled for an exam/re-sit means that you are not allowed to participate in the exam/re-sit.
Brightspace
Brightspace is the digital learning environment of Leiden University. Brightspace gives access to course announcements and electronic study material. Assignments will also be submitted in Brightspace. Students are advised to check Brightspace daily to remain informed about rooms, schedules, deadlines, and details of assignments. Lecturers assume that all students read information posted on Brightspace.
Please log in with your ULCN-account and personal password. On the left you will see an overview of My Courses.
You need to be enrolled for the respective courses to access them on Brightspace.
Contact
Course coordinator: Lotte de Vries
Study advisors: Kiki Boomgaard and Marisa Beunk
Remarks
BYOD and software
The BSc Science for Sustainable Societies has a ‘Bring Your Own Device’ policy. The Faculty of Science uses the software distribution platform Academic Software. Through this platform, you can access the software needed for specific courses in your studies. For some software, your laptop must meet certain system requirements, which will be specified with the software. It is important to install the software before the start of the course. More information about the laptop requirements can be found on the student website.