BKM_APS1 Applied Statistics 1

Faculty of Economics and Administration
Spring 2022
Extent and Intensity
26/0/0. 6 credit(s). Type of Completion: zk (examination).
Teacher(s)
Mgr. Lenka Zavadilová, Ph.D. (lecturer)
Guaranteed by
Mgr. Lenka Zavadilová, Ph.D.
Department of Applied Mathematics and Computer Science – Faculty of Economics and Administration
Contact Person: Lenka Hráčková
Supplier department: Department of Applied Mathematics and Computer Science – Faculty of Economics and Administration
Timetable
Fri 25. 2. 16:00–19:50 VT204, Sat 12. 3. 8:00–11:50 VT204, Fri 6. 5. 12:00–15:50 VT204
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
At the end of the course students should be able to:
- understand and explain the basic terms in calculus of probability and in descriptive statistics;
- apply the probability terms and the descriptive statistics terms to the description of economic events and data;
- use the terminology in the follow-up course of mathematical statistics.
Learning outcomes
After graduation of the course student should be able to:
- use and interpret functional and numeric characteristics within a framework of descriptive statistics
- describe types of variables with respect to measurement scale
- quantify randomness in elementary setting by probability
- use and properly interpret distributional function, probability function and density function
- determine in mathematical statistics popular distributions with respect to the application context
Syllabus
  • 1.Types of variables with respect to measurement scale. Data visualisation.
  • 2. Sampling, random sample
  • 3. Basic of descriptive statistics.
  • 4. Frequency and probability, probability properties, examples.
  • 5. Independent events, properties of independent events, sequence of independent events.
  • 6. Conditional probability, total probability rule, Bayes' theorem, examples.
  • 7. Random variable, a discrete and continuous variable, discrete probability distribution, probability function and its properties; continuous probability distribution, probability density function and its properties.
  • 8. Distribution function, its properties and its application.
  • 9. Numerical measures of probability distribution: expected value, variance, quantile, their properties and application in economics.
  • 10. Numerical measures of simultaneous probability distribution: covariance, correlation coefficient, their properties and application in economics.
  • 11. Examples of discrete and continuous probability distributions and their application in the field of economics.
  • 12. Central limit theorem and its applications.
  • 13. Review
Literature
    required literature
  • BUDÍKOVÁ, Marie, Maria KRÁLOVÁ and Bohumil MAROŠ. Průvodce základními statistickými metodami (Guide to basic statistical methods). vydání první. Praha: Grada Publishing, a.s., 2010, 272 pp. edice Expert. ISBN 978-80-247-3243-5. URL info
  • https://www.r-project.org/
  • KONEČNÁ, Kateřina and Jan KOLÁČEK. Jak pracovat s jazykem R (How to work with R language). 2011, 84 pp. info
    recommended literature
  • WEISS, N. A. Introductory statistics. Edited by Carol A. Weiss. 10th edition, global edition. Boston: Pearson, 2017, 763, 73. ISBN 9781292099729. info
  • BUDÍKOVÁ, Marie, Tomáš LERCH and Štěpán MIKOLÁŠ. Základní statistické metody. 1. vyd. Brno: Masarykova univerzita, 2005, 170 pp. ISBN 978-80-210-3886-8. info
  • CRAWLEY, Michael J. The R book. 2nd ed. Chichester: Wiley, 2013, xxiv, 1051. ISBN 9780470973929. info
  • https://www.r-bloggers.com
  • VERZANI, John. Using R for introductory statistics. Boca Raton: Chapman & Hall/CRC, 2005, xvi, 414. ISBN 1584884509. info
  • FIELD, Andy P., Jeremy MILES and Zoë FIELD. Discovering statistics using R. First published. Los Angeles: Sage, 2012, xxxiv, 957. ISBN 9781446200452. info
Teaching methods
Practically oriented tutorials with an emphasis on the active students' approach.
Individual study of recommended literature, autokorection tests, individual work on assigned tasks.
Assessment methods
To complete the course, the elaboration and defence of a semestral project are needed. In evaluation, the emphasis is placed on appropriate methods selection and performance, correct interpretation and presentation of results.
The course is completed by written exam consisting of theoretical and practical parts.
Language of instruction
Czech
Follow-Up Courses
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
Information on the extent and intensity of the course: tutorial 12 hodin.
Listed among pre-requisites of other courses
The course is also listed under the following terms Spring 2023, Spring 2024, Spring 2025.
  • Enrolment Statistics (Spring 2022, recent)
  • Permalink: https://is.muni.cz/course/econ/spring2022/BKM_APS1