M7521 Probability and Statistics

Faculty of Science
Autumn 2015
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
RNDr. Marie Budíková, Dr.
Department of Mathematics and Statistics – Departments – Faculty of Science
Supplier department: Department of Mathematics and Statistics – Departments – Faculty of Science
Timetable
Tue 8:00–9:50 M1,01017
  • Timetable of Seminar Groups:
M7521/01: Mon 8:00–9:50 M3,01023, Mon 8:00–9:50 MP1,01014, M. Budíková
M7521/02: Mon 12:00–13:50 M3,01023, Mon 12:00–13:50 MP1,01014, M. Budíková
Prerequisites (in Czech)
M4502 Mathematical Analysis 4
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
there are 7 fields of study the course is directly associated with, display
Course objectives
After completing this course, students
- can obtain information from the data file in the form of tables, graphs and numerical characteristics;
- understand the basic concepts of probability, such as classical, geometric and conditional probability;
- are able to use important discrete and continuous probability distributions in appropriate situations;
- can calculate the mean, variance, covariance and correlation coefficient of discrete and continuous random variables;
- will have a good knowledge of STATISTICA system.
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, correlation coefficient. 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.). 3rd ed. Brno: Masarykova univerzita, 2004, 127 pp. ISBN 80-210-3313-4. 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
During the semester, students write two tests. The examination is written with "open book". It consists of four examples. The examination is scored 100 points. To successfully pass the exam, 51 points will suffice.
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 2012, Autumn 2013, Autumn 2014, Autumn 2016, autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020.
  • Enrolment Statistics (Autumn 2015, recent)
  • Permalink: https://is.muni.cz/course/sci/autumn2015/M7521