OPF:INMBASTA Statistics - Course Information
INMBASTA Statistics
School of Business Administration in KarvinaSummer 2017
- Extent and Intensity
- 2/1/0. 6 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- prof. RNDr. Jaroslav Ramík, CSc. (lecturer)
Mgr. Radmila Krkošková, Ph.D. (seminar tutor)
doc. Mgr. Jiří Mazurek, Ph.D. (seminar tutor)
Ing. Elena Mielcová, Ph.D. (seminar tutor)
Ing. Radomír Perzina, Ph.D. (seminar tutor)
prof. RNDr. Jaroslav Ramík, CSc. (seminar tutor)
Ing. Filip Tošenovský, Ph.D. (seminar tutor) - Guaranteed by
- prof. RNDr. Jaroslav Ramík, CSc.
Department of Informatics and Mathematics – School of Business Administration in Karvina
Contact Person: Mgr. Radmila Krkošková, Ph.D. - Prerequisites
- No specific conditions and courses are required, however, the course should follow after the basic courses of calculus and information science.
- 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
- Banking (programme OPF, B_HOSPOL)
- Business Economics in Trade and Services (programme OPF, B_EKOMAN)
- 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 - qualitative variables
3. Descriptive statistics - quantitative variables
4. Elements of probability
5. Random variable
6. Discrete probability models
7. Continuous probability models
8. Point estimation
9. Confidence intervals
10. Hypotheses testing - parametric tests
11. Hypotheses testing - non-parametric tests
12. Analysis of variance - ANOVA
13. 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 - qualitative variables
Qualitative variables, frequency distribution, characteristics of central tendency, characteristics of variation.
3. Descriptive statistics - quantitative variables
Qualitative and quantitative variables, frequency distribution, characteristics of central tendency, characteristics of variation, variance, standard deviation.
4. Elements of probability
Random event, combinatorics, intuitive definition of probability, probability as a relative frequency, properties of probability.
5. Random variable
Discrete and continuous random variable, characteristics of random variable, characteristics of central tendency and variation (mean, variance and standard deviation)
6. Discrete probability models
Probability function, distribution function, uniform distribution, binomial distribution, Poisson distribution, other well known discrete distributions.
7. Continuous probability models
Density function, uniform distribution, normal distribution, lognormal distribution, exponential distribution other discrete distributions.
8. Point estimation
Point estimation and its properties.
9. Confidence intervals
Interval estimation and its properties, confidence intervals for the mean, variance and ratio.
10. Hypotheses testing - parametric tests
Statistical testing, kinds of hypotheses, one-sided and two-sided tests, test for the mean value, and the variance.
11. Hypotheses testing - non-parametric tests
Chi-square distribution, chi-square tests of goodness of fit, test of independence in the contingence tables.
12. Analysis of variance - ANOVA
One-way ANOVA, Fisher's distribution F, F-test for the mean, two-way ANOVA.
13. Simple regression analysis
Regression linear model, least squares method, linear regression function, prediction in time series.
- 1. Statistics and its importance
- Literature
- Teaching methods
- Skills demonstration
Seminar classes - Assessment methods
- Written exam
Written test - Language of instruction
- English
- Further comments (probably available only in Czech)
- The course can also be completed outside the examination period.
- Teacher's information
- written test, written exam test, 70% attendance at the seminars
Activity Difficulty [h] Ostatní studijní zátěž 91 Přednáška 26 Seminář 13 Zkouška 40 Summary 170
- Enrolment Statistics (Summer 2017, recent)
- Permalink: https://is.slu.cz/course/opf/summer2017/INMBASTA