OPF:MMEPKVBA Quantitative Methods B - Informace o předmětu
MMEPKVBA Quantitative Methods B
Obchodně podnikatelská fakulta v Karvinézima 2007
- Rozsah
- 2/1/0. 4 kr. Ukončení: zk.
- Vyučující
- Mgr. Šárka Čemerková, Ph.D. (přednášející)
prof. RNDr. Jaroslav Ramík, CSc. (přednášející)
Mgr. Šárka Čemerková, Ph.D. (cvičící)
Mgr. Radmila Krkošková, Ph.D. (cvičící)
Ing. Elena Mielcová, Ph.D. (cvičící)
Ing. Radomír Perzina, Ph.D. (cvičící)
prof. RNDr. Jaroslav Ramík, CSc. (cvičící)
Ing. Filip Tošenovský, Ph.D. (cvičící) - Garance
- prof. RNDr. Jaroslav Ramík, CSc.
Katedra informatiky a matematiky – Obchodně podnikatelská fakulta v Karviné - Omezení zápisu do předmětu
- Předmět je otevřen studentům libovolného oboru.
- Cíle předmětu
- 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.
- Osnova
- 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
- Literatura
- povinná literatura
- DANIEL, W.W., TERREL, J.C. Business statistics. Houghton Mifflin Co., Boston, 1996. info
- Vyučovací jazyk
- Angličtina
- Informace učitele
- test, 70% attendance at the seminars, exam test
- Další komentáře
- Předmět je dovoleno ukončit i mimo zkouškové období.
- Statistika zápisu (zima 2007, nejnovější)
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