OPF:MMEKKVBA Quantitative Methods B - Course Information
MMEKKVBA Quantitative Methods B
School of Business Administration in KarvinaWinter 2008
- Extent and Intensity
- 12/0/0. 4 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- Mgr. Šárka Čemerková, Ph.D. (lecturer)
Mgr. Radmila Krkošková, Ph.D. (lecturer)
Ing. Elena Mielcová, Ph.D. (lecturer)
Ing. Radomír Perzina, Ph.D. (lecturer)
Ing. Filip Tošenovský, Ph.D. (lecturer) - Guaranteed by
- prof. RNDr. Jaroslav Ramík, CSc.
Department of Informatics and Mathematics – School of Business Administration in Karvina - Course Enrolment Limitations
- The course is offered to students of any study field.
- Course objectives (in Czech)
- 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 (in Czech)
- 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.
- 1. Statistics and its importance
- Literature
- required literature
- DANIEL, W.W., TERREL, J.C. Business statistics. Houghton Mifflin Co., Boston, 1996. info
- Language of instruction
- English
- Further comments (probably available only in Czech)
- The course can also be completed outside the examination period.
- Enrolment Statistics (Winter 2008, recent)
- Permalink: https://is.slu.cz/course/opf/winter2008/MMEKKVBA