Admission requirements
There are no admission requirements.
Note:
This course is open to non-biology students. The datasets revolve around biological problems (ecology, medicine, genetics), but the statistical techniques apply across many fields.
This course is offered twice a year.
Description
From medical records to gene expressions to ecological field experiments, biology requires a large variety of statistical approaches. Basic Statistics for Master Students covers everything from basic comparisons to multiple linear regression, with a strong emphasis on generalized linear models (GLMs). GLMs are a flexible class of models that can handle a wide range of outcome types, making them a useful starting point for various types of biological research. You will also learn how to prepare, visualize, and analyze data using the open-source programming language R.
Statistical methods covered:
Univariate tests (t-test, chi-squared test, F-test)
Multiple testing correction
ANOVA
ANCOVA
Simple linear regression
Multiple linear regression
GLM
Introduction to mixed models
Should I choose Basic Statistics or Advanced Statistics?
Unlike Advanced Statistics, Basic Statistics assumes little background knowledge of statistics or programming. To make the choice easier, ask yourself the following questions:
Are you familiar with most of the statistical methods covered?
Do you have previous experience programming in R?
Unless you confidently answered yes to both questions, we recommend taking Basic Statistics first. Basic Statistics does not mean easy statistics, it is simply a stepping stone to our other master course named Advanced Statistics. If you obtained your bachelor's degree elsewhere, the course brings you up to speed with the level of statistics and R programming required for Advanced Statistics.
If you obtained your bachelor's degree at the IBL but are not required to follow Advanced Statistics (for example, because you are following the Biology and Business Studies master track), Basic Statistics still has a lot to offer: the course takes a different approach from the bachelor course, with a 2-day introduction to mixed models.
Course objectives
After completion of the course, students can:
- Recognize the correct definition of important concepts in statistics (false positive/negative, p-value).
- Explain a programming or statistical problem and solicit help from a statistical consultant.
- Calculate false positive rates.
- Perform basic statistical analyses themselves.
- Interpret output from statistical tests and models.
- Convert data to a tidy format, create subsets and evaluate the quality of collected data.
- Judge the validity of simple statistical analyses used in published articles.
- Design simple studies with maximal power and minimal risk of bias.
- Produce publication-grade figures and tables in R.
- Open, edit and run basic scripts in R, using RStudio, and use literate programming to compile a report that includes code, output and commentary.
- Work through unfamiliar formulas or code by breaking it into parts, rather than giving up when it looks complex.
Schedule
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.
Teaching method
Lectures, tutorials, computer workshops, Shiny apps, YouTube videos, quiz questions.
Assesment method
The final grade consists of the following partial grades: ● Written exam (75%) ● Assignment (25%)
Both must be done on site.
Minimum grade:
Both the exam and graded assignment require a minimum, unrounded 5,5 grade to complete the course.
For students retaking the course, if you passed the graded assignment no more than one year ago, you may have your previous grade count.
Please refer to theStudent Charter for an overview of regulations.
Resit, review & feedback
A resit will be held for both the exam and graded assignment. Please check the schedule, and keep an eye on Brightspace announcements for enrollment details.
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: 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
Coordinator: Frans Rodenburg & 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 in Ans and the graded assignment will have detailed feedback per group.
Brightspace will be used for communication, Q&A, and other course material.
You must have a laptop with administrator/installation rights. Tablets, Chromebooks and other devices that cannot install R and RStudio are not supported.