M7521 Probability and Statistics

Faculty of Science
Autumn 2012
Extent and Intensity
2/2/0. 3 credit(s) (příf plus uk k 1 zk 2 plus 1 > 4). Type of Completion: zk (examination).
Teacher(s)
RNDr. Marie Budíková, Dr. (lecturer)
Guaranteed by
doc. RNDr. Eduard Fuchs, CSc.
Department of Mathematics and Statistics – Departments – Faculty of Science
Supplier department: Department of Mathematics and Statistics – Departments – Faculty of Science
Timetable
Mon 10:00–11:50 M4,01024
  • Timetable of Seminar Groups:
M7521/01: Mon 14:00–15:50 M3,01023, Mon 14:00–15:50 MP1,01014, M. Budíková
Prerequisites (in Czech)
M4502 Mathematical Analysis 3
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
Descriptive statistics. Probability space, independent events, conditional probability. Random variables, their distribution and characteristics. Law of large numbers, central limit theorem. Upon completing this course, students will be able to perform basic statistical data set analysis. Furthermore, students will understand and will be able to apply important concepts of calculus of probabilities.
Syllabus
  • Descriptive statistics. Basic and sample file, scalar and vector variables, functional and numerical characteristics of these variables. Theory of probability. Empirical law of large numbers, axiomatic definition of probability, basic properties of probability, classical, geometrical and conditional probability, stochastic independet events. Random variables and random vectors, discrete and continuous distributions. Transformations of random variables. Quantil, expected value, variance, covariance. Law of large numbers, central limit theorem.
Literature
  • BUDÍKOVÁ, Marie, Štěpán MIKOLÁŠ and Pavel OSECKÝ. Popisná statistika (Descriptive Statistics). 3., doplněné vyd. Brno: Masarykova univerzita, 1998, 52 pp. ISBN 80-210-1831-3. info
  • BUDÍKOVÁ, Marie, Štěpán MIKOLÁŠ and Pavel OSECKÝ. Teorie pravděpodobnosti a matematická statistika. Sbírka příkladů. (Probability Theory and Mathematical Statistics. Collection of Tasks.). 2.,přepracované vyd. Brno: Masarykova univerzita Brno, 1998, 127 pp. ISBN 80-210-1832-1. info
  • OSECKÝ, Pavel. Pravděpodobnost a statistika. Vyd. 1. Praha: Státní pedagogické nakladatelství, 1988, 354 s. info
Teaching methods
The weekly class schedule consists of 2 hour lecture and 2 hours of class exercises with special statistical software in computer classroom.
Assessment methods
At the end of semester, students submit a written task. The examination is written, consisting of theoretical and practical parts.
Language of instruction
Czech
Follow-Up Courses
Further Comments
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Autumn 1999, Autumn 2010 - only for the accreditation, Autumn 2000, Autumn 2001, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2011 - acreditation, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020.
  • Enrolment Statistics (Autumn 2012, recent)
  • Permalink: https://is.muni.cz/course/sci/autumn2012/M7521