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Middle East Technical University Department of Statistics Spring 2008-2009 STAT 356 STATISTICAL DATA ANALYSIS Credit: (3-2) 4 Prerequisite Courses: STAT 156, STAT 291 Instructor: Dr. Özlem İLK, 134, Department of Statistics E-mail: [email protected] Phone: 210 53 26 Assistant: M.Tuğba ERDEM, 141, Department of Statistics Course Web page: http://www.metu.edu.tr/~oilk/s356.html Course Objectives: Recent advances in computers and computer sciences enabled researchers working in various fields to store and process huge amount of data. As a result, new methodologies have been developed for approaching huge and complex data. This computeraided course is designed to equip the students with the tools and techniques of handling massive data. It provides the students with the essential information for handling complex data. Textbooks: No specific textbook. Reference Books & Papers: Agresti, A., (2002) Categorical Data Analysis, 2nd edition, Wiley, New York. Chatfield, C., (1980) Problem Solving: A Statistician’s Guide, 2nd edition, Chapman & Hall. Hoaglin, D.C., Mosteller, F. and Tukey, J.W., (1983) Understanding Robust and Exploratory Data Analysis, Wiley. Neter, J., Kutner, M.H., Nachtsheim, C.J. and Wasserman, W., (1996) Applied Linear Statistical Models, 4th edition, Irwin. Tukey, J.W., (1977) Exploratory Data Analysis, Addison-Wesley. Dunham, M.H., (2002) Data mining: Introductory and advanced topics, Prentice Hall. Han, J. And Kamber,. M., (2000) Data mining: Concepts and techniques, Morgan Kaufmann Pub. Little, R.J.A and Rubin, D.B., (2002) Statistical Analysis with Missing Data, 2nd edition, Chichester:Wiley . Tentative Course Outline: Introduction Graphical and tabular representation of data Approaches to finding the unexpected in data Exploratory data analysis Analysis of categorical data Handling missing data Elements of robust estimation Smoothing methods Data mining Case Studies 1 Grading Policy: Homeworks Midterm Exam Final Exam Class Reports + Class Participation Attendance : 15 % : 30 % : 40 % : 10 % : 5% Do’s and Don’ts: You are expected to attend all classes and exams. No matter what the situation is, I have ZERO tolerance for plagiarizing (cheating). If one choose to copy other’s work, s\he chooses grade over learning and is unfair to her\his classmates. There will be legal consequences. Late homeworks will not be accepted. Please do not have last minute requests. Especially, don’t try to contact me right before exams. Please check your e-mails and course web page frequently. We may contact you via e-mail on subjects concerning class. Please respect our schedule. For discussions and questions, come during our office hours, or make an appointment in advance. No calls to my cell or home phone. 2