INMBPSTK Statistics

School of Business Administration in Karvina
Summer 2022
Extent and Intensity
2/1/0. 5 credit(s). Type of Completion: zk (examination).
Teacher(s)
Mgr. Radmila Krkošková, Ph.D. (lecturer)
Ing. Zuzana Neničková, Ph.D. (seminar tutor)
Ing. Lucie Waleczek Zotyková, Ph.D. (seminar tutor)
Guaranteed by
Mgr. Radmila Krkošková, Ph.D.
Department of Informatics and Mathematics – School of Business Administration in Karvina
Contact Person: Mgr. Radmila Krkošková, Ph.D.
Timetable
Mon 8:05–9:40 VS
  • Timetable of Seminar Groups:
INMBPSTK/01: Tue 8:55–9:40 B307, L. Waleczek Zotyková
INMBPSTK/03: Tue 8:05–8:50 B307, L. Waleczek Zotyková
INMBPSTK/06: Wed 9:45–10:30 A318, L. Waleczek Zotyková
INMBPSTK/07: Wed 8:05–8:50 B207, Z. Neničková
INMBPSTK/08: Wed 8:55–9:40 B207, Z. Neničková
INMBPSTK/09: Wed 9:45–10:30 B207, Z. Neničková
INMBPSTK/10: Wed 10:35–11:20 B207, Z. Neničková
Prerequisites (in Czech)
FAKULTA(OPF) && TYP_STUDIA(B) && FORMA(P)
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.

The capacity limit for the course is 200 student(s).
Current registration and enrolment status: enrolled: 2/200, only registered: 0/200
fields of study / plans the course is directly associated with
there are 12 fields of study the course is directly associated with, display
Course objectives
The course objective is to teach the students the principles of mathematical and economical statistics. The course acquaints students with the basic mathematical and statistical methods of data analysis with respect to real applications in economy. The course follows after the basic courses of calculus and information science. The student should acquire also appropriate calculation skills and should be able to solve statistical problems by Excel on PC. It leads to the creating of the essential profile of all students at the School of Business Administration. At the same time it is the base of the university education of further economic courses on the bachelor's as well as the master's study.
Syllabus
  • 1. Statistics and its importance
    2. Descriptive statistics - quantitative and qualitative variables
    3. Elements of probability
    4. Random variable
    5. Discrete probability models
    6. Continuous probability models
    7. Point estimation
    8. Confidence intervals
    9. Hypotheses testing - parametric tests
    10. Hypotheses testing - non-parametric tests
    11. Analysis of variance - ANOVA
    12. Simple regression analysis
    1. Statistics and its importance
    Statistical methods in business and entrepreneurship, descriptive and inductive statistics, statistics in decision making.
    2. Descriptive statistics - quantitative and qualitative variables
    Qualitative and quantitative variables, frequency distribution, characteristics of central tendency, characteristics of variation, variance, standard deviation.
    3. Elements of probability
    Random event, combinatorics, intuitive definition of probability, probability as a relative frequency, properties of probability.
    4. Random variable
    Discrete and continuous random variable, characteristics of random variable, characteristics of central tendency and variation (mean, variance and standard deviation)
    5. Discrete probability models
    Probability function, distribution function, uniform distribution, binomial distribution, Poisson distribution, other well known discrete distributions.
    6. Continuous probability models
    Density function, uniform distribution, normal distribution, lognormal distribution, exponential distribution other discrete distributions.
    7. Point estimation
    Point estimation and its properties.
    8. Confidence intervals
    Interval estimation and its properties, confidence intervals for the mean, variance and ratio.
    9. Hypotheses testing - parametric tests
    Statistical testing, kinds of hypotheses, one-sided and two-sided tests, test for the mean value, and the variance.
    10. Hypotheses testing - non-parametric tests
    Chi-square distribution, chi-square tests of goodness of fit, test of independence in the contingence tables.
    11. Analysis of variance - ANOVA
    One-way ANOVA, Fisher's distribution F, F-test for the mean, two-way ANOVA.
    12. Simple regression analysis
    Regression linear model, least squares method, linear regression function, prediction in time series.
Literature
    required literature
  • RAMÍK, J. a R. STOKLASOVÁ. Statistika. Karviná: SU OPF, 2012. ISBN 978-80-7248-198-3. info
    recommended literature
  • RAMÍK, J. a Š. ČEMERKOVÁ. Statistika A. Karviná: SU OPF, 2000. ISBN 80-85879-43-3. info
  • RAMÍK, J. a Š. ČEMERKOVÁ. Statistika B. Karviná: SU OPF, 2000. ISBN 80-7248-001-4. info
  • CYHELSKÝ, L., J. KAHOUNOVÁ a R. HINDLS. Elementární statistická analýza. Praha: Management Press, 1996. ISBN 80-7261-003-1. info
  • SEGER, J. a R. HINDLS. Statistické metody v tržním hospodářství. Praha: Victoria Publishing, 1995. ISBN 80-7187-058-7. info
  • WONNACOT, T. H. and J. W. WONNACOT. Introductory statistics for business and economics. New York: Wiley and Sons, 1990. ISBN 0-4716-1517-X. info
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course can also be completed outside the examination period.
Teacher's information
On the seminars a corresponding numerical statistical experience on PC computers with Excel is required. During the 5th and 8th week of the semester a written tests are performed, the obtained score is added to the total score of the final evaluation. The 70% attendance at the seminars is asked.
The course is also listed under the following terms Summer 2016, Summer 2017, Summer 2018, Summer 2019, Summer 2020, Summer 2021, Summer 2023, summer 2024.
  • Enrolment Statistics (Summer 2022, recent)
  • Permalink: https://is.slu.cz/course/opf/summer2022/INMBPSTK