Course detail
Statistics 2
FP-STA2Acad. year: 2023/2024
Students will acquire basic knowledge of mathematical statistics, categorical and correlation analysis, analysis of variances, regression analysis and time series analysis.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Entry knowledge
Students will gain knowledge of 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
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).
Attendance at lectures is not mandatory but is recommended. Attendance at exercises is required and checked by the tutor.
Aims
Students will acquire basic knowledge of mathematical statistics, categorical and correlation analysis, analysis of variances, regression analysis and time series analysis.
At the end of the course students will be able to use these methods in master's courses and in the real managerial problems.
Study aids
Prerequisites and corequisites
Basic literature
Studijní materiály vystavené na e-learningu.
Recommended reading
FIELD, A., J. MILES and Z. FIELD. Discovering Statistics Using R. 1 edition. Los Angeles, Calif.: SAGE Publications Ltd., 2012. ISBN 978-1-4462-0046-9.
JAMES, G., D. WITTEN, T. HASTIE a R. TIBSHIRANI. An Introduction to Statistical Learning: with Applications in R. New York: Springer New York, 2014. 426 s. ISBN 978-1-4614-7137-0.
Elearning
Classification of course in study plans
- Programme BAK-MIn Bachelor's 2 year of study, summer semester, compulsory
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
2. Empirical distribution function
3. Analysis of large data sets
4. Point and interval estimates
5. Testing statistical hypothesis
6. Correlation analysis
7. Categorical analysis
8. Analysis of variance
9. Linear regression models
10. Nonlinear regression models (linearizable functions)
11. Nonlinear regression models (non-linearizable functions)
12. Time serie analysis
13. Time serie decomposition and identify its trend
Exercise
Teacher / Lecturer
Syllabus
Elearning