A 2.5 day-course in Astrostatistics and R programming by Prof. Eric Feigelson (Penn State)

April 23, 24 , 9:30 am- 17:00 pm and April 25 9:30 - 12:30 a.m., IAP (seminar room)

Astronomers face data and science analysis problems that require a wide range of statistical analyses. Modern statistics is vast in its capabilities, but is often opaque to scientists with limited training in methodology. This Short Course provides a foundation in statistical inference and practice upon which research problems can be tackled. It also trains participants in R, an enormous and comprehensive statistical software environment developed by experts in statistical computing that is freely available to the public (www.r-project.org). The methodology lectures and hands-on software tutorials are integrated together with applications using contemporary astronomical datasets.

Wednesday 23 April

0930-1030 Astrostatistics: Past, present and future [general lecture]
1100-1230 Introduction to the R statistical computing environment [lecture and tutorial]
1400-1500 Density estimation (or data smoothing) [lecture and tutorial]
1530-1700 Principles of statistical inference [lecture]

Thursday 24 April

0930-1030 Regression [lecture and tutorial]
1100-1230 Multivariate analysis and visualization [lecture and tutorial]
1400-1500 Data mining: Clustering and classification [lecture and tutorial]
1530-1700 Spatial point processes [lecture and tutorial]

Friday 25 April

0930-1030 Towards good statistical practice in astronomical research [general lecture]
1100-1230 Time series analysis (evenly and unevenly spaced data) [lecture and tutorial]

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