JTW > Courses > ASTP 611: Statistical Methods for Astrophysics
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NOTE

This is the webpage for a prior semester's section of Stat Methods. If you're looking for information on my most recent section of the course, please go to http://ccrg.rit.edu/~whelan/ASTP-611/

Vital Statistics

Lecture Room

Tuesday: CAR(76)-1155

Thursday: GOL(70)-1445

Class Times

Tuesday & Thursday, 09:30-10:45

Required Textbook

• Gregory, Bayesian logical data analysis for the physical sciences, First Edition (Cambridge, 2005). ISBN 978-0-52-184150-4

Recommended Textbooks

• Sivia with Skilling, Data analysis: a Bayesian tutorial, Second Edition (Oxford, 2006). ISBN 978-0-19-856832-2
  Also available as an electronic book through the Wallace Library.

Other Useful References

• Wall and Jenkins, Practical statistics for astronomers, First Edition (Cambridge, 2003). ISBN 978-0-52-145616-6
• Wasserman, All of statistics: a concise course in statistical inference, First Edition (Springer, 2005). ISBN 978-0-38-740272-7
• Cowan, Statistical Data Analysis, First Edition (Oxford, 1998). ISBN 978-0-19-850155-8
• Jaynes, Probability Theory: The Logic of Science, First Edition (Cambridge, 2003). ISBN 978-0-52-159271-0
• Casella and Berger, Statistical Inference, Second Edition (Brooks-Cole/Cengage, 2002). ISBN 978-0-53-424312-8
• Bendat and Piersol, Random Data: Analysis & Measurement Procedures Third Edition (Wiley, 2000) ISBN 978-0-47-131733-3
• Press, Teukolsky, Vetterling, and Flannery, Numerical Recipes Third Edition (Cambridge, 2007) ISBN 978-0-52-188407-5
  • Second edition available free online
• Arfken, Weber, and Harris, Mathematical Methods for Physicists, Seventh Edition: A Comprehensive Guide , Seventh Edition (Academic Press, 2012). ISBN 978-0-12-384654-9

Course Webpage

http://ccrg.rit.edu/~whelan/ASTP-611/ (this page)

Instructor

Dr. John T. Whelan

74-2063, 5-5083

john.whelan@astro.rit.edu

Office Hours

TBA

Syllabus

Course Calendar

A tentative timetable is given in the Course Calendar.

Lecture Notes

• Fourier Methods
  • See also Exercises on Fourier Series
  • ipython notebook for plotting discretization kernel
• Probability Theory
  • ipython notebook on simulating a Poisson process
• Statistical Inference
  • ipython notebook with monte carlo demo
  • ipython notebook with MCMC demo using trinomial distribution

Homework Assignments

• Problem Set 1 -- Due 2014 February 6
  • ipython notebook for problem 2.2
• Problem Set 2 -- Due 2014 February 11
  • ipython notebook for problem 1
• Problem Set 3 -- Due 2014 February 20
• Problem Set 4 -- Due 2014 February 27
  • ipython notebook for problem 2
• Problem Set 5 -- Due 2014 March 13/18
• Problem Set 6 -- Due 2014 April 1
• Problem Set 7 -- Due 2014 April 10
  • ipython notebook for problem 2
• Problem Set 8 -- Due 2014 April 17
  • data file for problem 1
  • ipython notebook for problem 3
• Problem Set 9 -- Due 2014 April 29
  • ipython notebook for problem 2
• Problem Set 10 -- Due 2014 May 8
  • ipython notebook for problem 2
• Problem Set 11 -- Due 2014 May 13

Links

• 1060-710, Math/Stat Methods, Fall 2010
• 1060-710, Math/Stat Methods, Fall 2009
• Python
  • SciPy
    • NumPy
    • ipython
  • matplotlib
  • Bundled distributions of the above python tools (especially useful for Mac & Windows users)
    • Enthought Python Distribution (free academic license, must be renewed annually)
    • Anaconda (basic installation is free)
  • Cloud-based python/ipython services:
    • Wakari
  • AstroPython
• R (computing language)
  • R tutorial
• Center for Astrostatistics