Admission requirements
Familiarity with least-squares analysis (Praktische Sterrenkunde). Basic Python skills such as: making figures, working with functions, for-loops, and executing scripts (Programmeermethoden NA).
Description
After you have conducted observations, and have finished reducing these into what we call a dataset, follows an important question: what can you learn from these data? Perhaps you have a certain hypothesis that needs to be tested. Or perhaps you have stumbled on a potential correlation between two observables of your sample. For each of these scenarios a set of tools is available to assess the relevance of your observations. In Statistics and Data Analysis you will get familiar with these assessment tools. By creating your own simulated datasets you will understand how and why these tools work, and also find out about their limitations. Finally, you will work with real astronomical datasets and apply what you have learned in practice.
Course objectives
You will learn how to simulate data using a Monte Carlo approach, you will also test the boundaries of statistical methods, thus learning how to avoid common problems such as “overfitting” and the “look-elsewhere effect”.
After this course, you are able to:
Simulate data using Monte Carlo methods.
Apply two different statistical tests (Pearson’s r and Kendall’s tau) to measure the correlation strength between two variables.
Apply two different statistical tests to examine the difference between two distributions (Kolmogorov-Smirnov and Anderson-Darling).
Explain how these tests work and under which circumstances they can be applied.
Explain the difference between a correlation and causal connection.
Identify when the “look-elsewhere” effect is important in your data analysis.
Quantify when you are “overfitting” the data.
Ability to ask the right questions about your dataset.
Visualizing key properties of a dataset in a clear figure.
Structured thinking, including computational thinking and programming.
Summarizing the properties of a dataset in a written report.
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
Exercise classes
All the exercise classes will involve writing and running scripts in Python. A laptop with a working Python environment is preferred for these classes.Mandatory reading material with quiz and discussion questions
Assessment method
Two homework sets (50%)
Written report for final assessment (50%)
Reading list
Background material will be made available during the course.
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
Lecturer: Dr. S. van Velzen
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.