The course will present fundamental notions in statistics and specific statistical techniques with applications to astronomical research. The topics covered are the basics of probability theory, point estimation, confidence intervals, hypothesis testing, regression, and others. Methods will be illustrated using the statistical software package R.
The course aims at introducing students to fundamental notions of statistics and familiarizing them with specific statistical techniques applied in astronomical research. Relevant methods will be illustrated using the statistical software package R. Upon completion of the course, the student will have knowledge of the basics of probability theory, point estimation, resampling methods, confidence intervals, hypothesis testing, regression, and others. Students will also acquire knowledge of the principles of R and will learn to use it in practical solution of several standard statistical tasks.
In this course, students will be trained in the following behaviour-oriented skills:
Problem solving (recognizing and analyzing problems, solution-oriented thinking)
Analytical skills (analytical thinking, abstraction, evidence)
Structured thinking (structure, modulated thinking, computational thinking, programming)
Complex ICT-skills (data analysis, programming, simulations, complex ICT applications)
Written communication (writing skills, reporting, summarizing)
Critical thinking (asking questions, check assumptions)
Integrity (honesty, moral, ethics, personal values)
See Schedules bachelor Astronomy 2017-2018
Mode of instruction
Homework assignments (30%) and written exam (70%).
A minimum grade of 5.0 on homework assignments is required to take the written exam.
See Examination schedules bachelor Astronomy 2017-2018
Lecture notes, additional readings and assignments will be provided on Blackboard.
To have access, you need an ULCN account. More information:
All of Statistics. Larry Wasserman (corrected second printing, 2005), ISBN 9780387402727. Click title to download electronic version through Leiden University Libraries.
Practical Regression and Anova in R, Faraway. Click title to download electronic version.
Bayesian Methods for the Physical Sciences, Andreon & Weaver, ISBN 9783319152868. Click title to download electronic version through Leiden University Libraries.
Nonlinear Regression with R, Ritz & Streibig, ISBN 9780387096155. Click title to download electronic version through Leiden University Libraries.
Register via uSis. More information about signing up for classes and exams can be found here. Exchange and Study Abroad students, please see the Prospective students website for information on how to register. For a la carte and contract registration, please see the dedicated section on the Prospective students website.
Lecturer: Dr. S. (Shota) Gugushvili
Course website: Statistics AN