Admission requirements
A signed research project agreement must be shown at the start of the course.
Description
Statistics is fundamental to biological research—not only for analyzing data, but also for designing robust studies. Whether through tables, visualizations, or written summaries, statistics helps communicate findings clearly and accurately. But its role starts long before data analysis: Issues like sampling bias, confounding variables, and underpowered studies can often be avoided by incorporating statistical thinking at the earliest stages of research.
This course starts with a one-week buildup to generalized linear models (GLM). This is a class of models that allows you to study processes of various natures, including continuous processes, counts, ratios and binary data. Another advantage of learning about GLMs is that many more complex forms of regression are “GLM-like,” and further build upon the general principles you learn in this course. In the second week, we will show you how to perform all kinds of comparisons with GLMs (including t-tests, ANOVA-style comparisons and ANCOVA-style comparisons). The third week focuses on covering other important topics and consolidating your knowledge from the first two weeks. It also includes a graded assignment for you to demonstrate your analysis skills developed so far.
We will use the open-source statistical programming language R. An installation/updating guide can be found here: https://youtu.be/jvL10YqZSEA (5 min.)
Statistics 2 is an intensive course, especially during the first two weeks. We expect you to be present during the computer workshops. Unless agreed upon with the study advisor, the BRP starts after, not during this course. If you must miss any workshops, please inform the coordinators in advance.
Course objectives
After completion of the course, students can:
1. Apply statistical analysis with GLMs in the context of their internship.
2. Recognize the correct definition of important concepts in statistics (false positive/negative, p-value).
3. Evaluate the quality of collected data both visually and numerically.
4. Choose an appropriate method from among the tests and models covered in the course.
5. Describe statistical methodology used and defend the choice of model.
6. Open, edit and run basic scripts in R, using RStudio, and use literate programming with Quarto to compile a report that includes code, output
and commentary.
7. Write precisely and scientifically about the results of an analysis and provide an interpretation of these results to answer the research question.
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.
Note: Joint Degree students from Leiden/Delft need to combine information from both the Leiden and Delft MyTimetables to see a complete schedule. This video explains how to do it.
Mode of Instruction
Lectures, tutorials, assignments and modules during Bachelor Research Project.
Assessment method
The final grade consists of the following partial grades:
● Written exam (75%)
● Assignment (25%)
Both must be done on site.
Minimum grade:
Courses require a minimum, unrounded 5.5 grade to complete.
If a course has 2 or more written partial exams, the minimum grade only applies to the weighted average of the exams.
For partial grades from components other than exams (e.g. practicals, seminars, writing assignments), the bottom grade does apply to the individual components.
Please refer to the Student Charter for an overview of regulations.
Reading list
An online ebook accompanying the course is available here:
https://fransrodenburg.github.io/Applied-Statistics/
In preparation, please perform a fresh install of the necessary software as explained here: https://youtu.be/jvL10YqZSEA
Registration
As a student, you are responsible for enrolling on time through MyStudyMap.
In this short video, you can see step-by-step how to enrol for courses in MyStudyMap.
Extensive information about the operation of MyStudyMap can be found here.
There are two enrolment periods per year:
Enrolment for the fall opens in July
Enrolment for the spring opens in December
See this page for more information about deadlines and enrolling for courses and exams.
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/resit means that you are not allowed to participate in the exam/resit.
Exchange and Study Abroad students, please see the Prospective students website for more information on how to apply.
Contact
Coördinator: Frans Rodenburg en Patrick van Hage
E-mail: f.j.rodenburg@biology.leidenuniv.nl, p.van.hage@biology.leidenuniv.nl
Remarks
Inspection and feedback on the examination: exam can be reviewed and discussed during a class session, and assignments can be reviewed in person.
Brightspace will be used for communication, Q&A, lecture summaries, screencasts, and handouts.
Software
Starting from the 2024/2025 academic year, the Faculty of Science will use 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.