Statistics S520 

Contact:  Brad Luen bradluen@indiana.edu 
Offered:  Spring, 2016 
Class Time:  45:15 pm 
Class Days:  Tu, Th 
Sequence:  No specific sequence. For students new to statistics, S520 is the preferred gateway to more advanced courses offered by the statistics department. 
PreRequisites:  The course catalog lists a year of calculus (MATHM 211212) as a formal prerequisite, but it should be noted that S520 is NOT a calculusbased course. No previous knowledge of calculus is required to complete S520, but the course alludes to several fundamental concepts from calculus (limit, area under curve). The purpose of the prerequisite is to screen out students who are afraid of formulas and mathematical notation, as such students typically find S520 too challenging. 
Algebra Required:  None. 
Calculus Required:  A few concepts only. 
Contact Person for Authorization:  Instructor 
Instructor:  Brad Luen bradluen@indiana.edu 
Website:  http://mypage.iu.edu/~mtrosset/320.html 
Recommended followup classes:  STATS 631632 (Applied Linear Models I & II). Students interested in learning more about statistical theory should follow S520 with MATHM 463 (Introduction to Probability Theory), then STATS 620 (Introduction to Statistical Theory). 
Syllabus:  Download Syllabus 
Keywords:  statistical inference, tests, confidence intervals, location problems, association, regression 
Description:  This course introduces the basic concepts of statistical inference through a careful study of several important procedures. Topics include 1 and 2sample location problems, the oneway analysis of variance, and simple linear regression. Most assignments involve applying probability models and/or statistical methods to practical situations and/or actual data sets. 
Books:  An Introduction to Statistical Inference and Its Applications with R, by Michael Trosset. Chapman & Hall/CRC, 2009. Here is the web page for the text: http://mypage.iu.edu/~mtrosset/StatInfeR.html 
Substantive Orientation:  Designed to accommodate students from a variety of disciplines. 
Statistical Orientation:  This course emphasizes a frequentist perspective. It covers conditional probability and Bayes theorem, but not Bayesian inference. 
Applied/Theoretical:  Intermediate. S520 emphasizes applications of statistical inference, but tries to communicate a deeper understanding of fundamental principles than does a typical introductory statistics text. For this reason, S520 initially strikes some students as somewhat theoretical. It emphasizes the assumptions that underlie common statistical practices. For example, Student's 2sample ttest assumes equal population variances, whereas Welch's approximate ttest does not. Is that fact an obscure bit of statistical theory or a useful guide to good statistical practice? 
Software:  R 
How Software is Used:  A distinctive feature of S520 is interactive computing. 
Problem Sets:  Weekly, for 25% of the semester average. 
Data Analysis:  Yes, typically involving real data sets. 
Presentation:  No. 
Exams:  Historically, two midterm tests and a final exam. 