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Course detail
FP-BAASEAcad. year: 2023/2024
Students will gain a basic understanding of discrete, continuous random variables and their important distribution types, processing of quantitative and qualitative trait data sets, point and interval estimation, the most used parametric and goodness-of-fit tests, simple and composite indices, linear and nonlinear regression models, and time series analysis.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Offered to foreign students
Entry knowledge
Students will gain knowledge of random variables, mathematical statistics, categorical and correlation analysis, analysis of variance, regression analysis and time series analysis and their use in business process management. Emphasis is primarily placed on the practical part, which is aimed at familiarizing with the use of statistical programs in the implementation of the above-mentioned methods and procedures.
Rules for evaluation and completion of the course
The course-unit credit is awarded on the following conditions (max. 40 points):- elaboration of semestral assignments.
The exam (max. 60 points)- has a written form.In the first part of the exam student solves 4 examples within 100 minutes. In the second part of the exam student works out answers to a theoretical question within 15 minutes.
The mark, which corresponds to the total sum of points achieved (max 100 points), consists of:- points achieved in semestral assignments,- points achieved by solving examples,- points achieved by answering theoretical questions.
The grades and corresponding points:A (100–90), B (89–80), C (79–70), D (69–60), E (59–50), F (49–0).
COMPLETION OF THE COURSE FOR STUDENTS WITH INDIVIDUAL STUDY
Attendance at lectures is not mandatory but is recommended. Attendance at seminars is controlled.
Aims
Study aids
Prerequisites and corequisites
Basic literature
Recommended literature
Elearning
Classification of course in study plans
branch BAK-ESBD , 1 year of study, summer semester, compulsory
branch BAK-Z , 1 year of study, summer semester, elective
Lecture
Teacher / Lecturer
Syllabus
1. Discrete and continuous random variable (basic concepts, empirical and function characteristics)2. Important type of distributions (Binomial distribution, Poission distribution, Gauss distribution, Exponential distribution...)3. Bivariate random variables (correlation)4. Descriptive statistics (basic concepts, empirical characteristics, empirical distribution function)5. Data sample analysis6. Parameters’ estimation (point and interval estimates)7. Test of statistical hypothesis (basic concepts and procedure)8. Basic parametric tests (t-test, F-test, ANOVA)9. Index analysis10. Individual and composite indexes11. Linear regression model (basic concepts, the least square method)12. Non-linear regression model (linearizable and non-linearizable regression models)13. Time series analysis (basic characteristics, decomposition)
Exercise
The topics of exercises correspond to the topics of lectures.