Statistics I

General data

Course ID:	1000-115ST1b
Erasmus code / ISCED:	11.1 Kod klasyfikacyjny przedmiotu składa się z trzech do pięciu cyfr, przy czym trzy pierwsze oznaczają klasyfikację dziedziny wg. Listy kodów dziedzin obowiązującej w programie Socrates/Erasmus, czwarta (dotąd na ogół 0) – ewentualne uszczegółowienie informacji o dyscyplinie, piąta – stopień zaawansowania przedmiotu ustalony na podstawie roku studiów, dla którego przedmiot jest przeznaczony. / (0541) Mathematics The ISCED (International Standard Classification of Education) code has been designed by UNESCO.
Course title:	Statistics I
Name in Polish:	Statystyka I (potok II)
Organizational unit:	Faculty of Mathematics, Informatics, and Mechanics
Course groups:	Obligatory courses for 3rd grade JSIM (3M+4I) Obligatory courses for 3rd grade Mathematics
ECTS credit allocation (and other scores):	(not available) Basic information on ECTS credits allocation principles: the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS; the student’s weekly hourly workload is 45 h; 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes; weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS; work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load. view allocation of credits
Language:	Polish
Type of course:	obligatory courses
Short description:	The aim of the course is to present fundamental concepts and methods of statistics. The course covers: population characteristics and their sample counterparts, stucture of statistical models from frequentist and Bayesian perspectives, problems of parametric and nonparametric estimation, testing statistical hypotheses, regression, classification/discriminant analysis.
Full description:	The aim of the course is to present in a concise manner fundamental concepts and methods of statistics, regarded as a science of inference from data. The emphasis is on applications and methodology of statistical inference rather than on technicalities. Some results are presented without proofs or only sketched. The course is illustrated with examples of statistical analyses. The course covers: empirical distributions, population characteristics and their sample counterparts, stucture of statistical models from frequentist and Bayesian perspectives, problems of parametric and nonparametric estimation, testing statistical hypotheses, regression, classification/discriminant analysis.
Bibliography:	Literature: M. Lavine, "Introduction to Statistical Thought", www.stat.duke.edu/~michael/book.pdf S.D. Silvey, "Statistical Inference", Wiley, 1970.

This course is not currently offered.

Course descriptions are protected by copyright.
Copyright by University of Warsaw.