Admission requirements
The topics covered in this course require a good knowledge and solid understanding of: calculus (derivatives and integrals), probability calculus, inferential statistics (point estimation, likelihood theory, confidence intervals, hypothesis testing), and programming with R. The courses “Mathematics for Statisticians”, “Statistics and Probability” and “Statistical Computing with R” from the MSc in Statistics and Data Science are prerequisites for this course. Students are also expected to have a basic understanding of the linear and logistic regression models.
Description
This course will introduce you to the field of computational statistics, which can be loosely defined as a set of numerical methods and algorithms that can be employed to solve a well-defined statistical problem. We will discuss the mathematical and statistical foundations that such methods rely on, and show how you can implement them in R.
The course will cover the following topics:
1. Methods for the generation of random variables
2. The Monte Carlo method
3. Applications of the Monte Carlo method
4. Variance reduction methods
5. Numerical integration and root finding algorithms
6. The bootstrap
7. Applications of the bootstrap
8. Permutation tests
Course Objectives
By the end of the course, students are expected to
1. understand the mathematical and statistical foundations of the methods covered in the course (see “Description”);
2. be able to recognize when a method can be applied to solve a given problem;
3. know how to solve relevant statistical problems using such methods;
4. be able to implement the methods and algorithms using R;
5. be able to interpret critically the results yielded by the application of such methods.
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
A combination of lectures and computer practicals. To fully benefit from the practicals, it is recommended that you bring your own laptop with R and RStudio installed.
Assessment method
A written exam at the end of the course.
Reading list
Rizzo, M. L. (2019). Statistical Computing with R. CRC Press.
When relevant, additional references will be provided at the end of each lecture.
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.
Contact
Remarks
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.