ASTR 3800 DATA ANALYSIS AND COMPUTING
TIME & PLACE: Monday, Wednesday 3:30-5:00 SBO
INSTRUCTOR: Webster Cash Duane D245 email@example.com
TA: Shalmali Barki Duane E122 firstname.lastname@example.org
HOURS: Before and after class or by appointment.
Statistics and Analysis of Scientific Data, Massimiliano Bonamente
Recommended: An Introduction to Error Analysis, John Taylor
Python for Everyone, Horstmann & Necaise
Statistics, Data Mining and Machine Learning in Astronomy, Ivezic, Connolly, VanderPlas & Gray
Data Reduction and Error Analysis for the Physical Sciences, Bevington and Robinson
EXAMS: No Exams.
HOMEWORK: There will be homework assignments on a regular basis. They will be graded and will count toward your course grade. Doing these problems is the core of the course. By working through the problems you will become facile with applications programming.
PROJECT: Before Spring Break you will need to choose some kind of project. The project will involve writing a system of linked Python procedures that will be useful in some context. For example: a statistical analysis package, or a photo image analysis system, or an astronomy simulation system. The project will be due after Spring Break and no later than the last day of class.
COURSE GRADE: Your grade will be based upon the homeworks grades and the project grade in roughly equal proportion. Precise balance will be announced mid-semester.
PREPARATION: Freshman level physics and integral calculus will prove very helpful but are not specifically required. It is expected that you have basic computer programming skills. It is advantageous to have Python experience, but not necessary. It is assumed that you have taken ASTR2600 or have equivalent skills.
COMPUTING: Access to
the workstations and Unix-based computers of the Observatory is
provided. However, most students prefer to install Python (for
free) on their laptops and work there. Help will be provided to
get that going during the first week of class if needed.