deletions | additions       diff --git a/integration-lecture-lab.tex b/integration-lecture-lab.tex  index 9c0aa51..83ab6ab 100644  --- a/integration-lecture-lab.tex  +++ b/integration-lecture-lab.tex 
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AST 208 was formed by merger of a laboratory observing course with a lecture-based course on planetary science. This merger was done to use available faculty hours efficiently; in practice the lecture and lab continued to operate as independent courses. Recent revisions to the lab (\S~\ref{s.encounters-with-data}), especially the use of ``real'' data, demand a more rigorous treatment of statistics, however, and therefore a tighter integration of the course lectures with the lab activities. To do this, we converted the first half of the course lectures into a more general discussion of astronomy and statistics. As motivation, we introduce these concepts in the context of detecting exoplanets; this ties the introductory material to the treatment of planetary science in the latter half of the course.  The first two weeks of lecture now discusses angular coordinates, right ascension and declination, sidereal time, and parallax. In the first lab, students find objects on the sky using with the \href{http://www.stellarium.org/}{\verb|Stellarium| planetarium software}; in the second lab, the students determine which celestial objects are visible from the MSU campus observatory. The lectures then discuss the inverse-square-law for flux, magnitude, and the distance modulus. A discussion of the wave nature of light, in particular diffraction, then follows. This dovetails with the lab, in which students use the \href{http://ds9.si.edu/site/Home.html}{\verb|ds9| visualization software} to measure point-spread functions.  The Following these topics, the next three weeks of  lectures then are devoted to probability and statistics. Starting with a derivation of probability rules from set-theoretical concepts, we  discuss the inverse-square-law for flux, magnitude, combinatorics  and the distance modulus. A discussion then build to a derivation  of the wave nature of light, binomial distribution  in particular diffraction, the context of the random walk. The small-probability limit as a Poisson distribution is introduced, and  then follows. This dovetails we imagine measurement fluctuations as a random walk  with a corresponding normal distribution. From there, we use maximum likihood concepts to derive  the lab, uncertainty  in which students the mean, propagation of uncertainties, and the  use of  the \href{http://ds9.si.edu/site/Home.html}{\verb|ds9| visualization software} to measure point-spread functions. $\chi^2$-statistic.