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# hw6 - UCF Physics AST 5765/4762(Advanced Astronomical Data...

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UCF Physics: AST 5765/4762: (Advanced) Astronomical Data Analysis Fall 2009 Homework 6 Due Tuesday 6 October 2009 Work: Become sufficiently familiar with fitting to: 1. Understand how the maximum likelihood method leads to least squares for Gaussian errors. 2. Fit linear models to data. 3. Use Python routines to fit more-complex models to data. 4. Decide whether to believe a fit. Become sufficiently familiar with CCDs to: 1. Understand conceptually how CCDs work. 2. Understand the sources of systematic and random error in CCD data. 3. Display and explore an astronomical image with Python and ds9 . Resources: 1. AST 5765 only: Chapter 15 of Press especially 15.6 and 15.8 ( DUE before class Tuesday, 6 October 2009). Skim/skip sections covered by Bevington. 2. /home/ast5765/python/linfit.py 3. /home/ast5765/python/gaussian.py 4. AST 5765 only: Understand all of linfit.py , especially the covariance matrix and the probability. Hand in: 1. Create a sample of 100 draws from the uniform distribution between 0 and 10. These are x values. Calculate f ( x ) = 3 . 2 x + 1 . 2 . Create a sample of 100 draws from the Gaussian

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hw6 - UCF Physics AST 5765/4762(Advanced Astronomical Data...

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