230-0322/01 – Applied statistics (AS)
Gurantor department | Department of Mathematics | Credits | 5 |
Subject guarantor | Ing. Veronika Moškořová, Ph.D. | Subject version guarantor | Ing. Veronika Moškořová, Ph.D. |
Study level | undergraduate or graduate | Requirement | Choice-compulsory type B |
Year | 1 | Semester | winter |
| | Study language | English |
Year of introduction | 2019/2020 | Year of cancellation | |
Intended for the faculties | FBI | Intended for study types | Bachelor, Follow-up Master |
Subject aims expressed by acquired skills and competences
The aim of the course is to provide theoretical and practical foundation for understanding the importance of basic probability concepts and teach the student statistical thinking as a way of understanding the processes and events around us, to acquaint him with the basic methods of gathering and analyzing statistical data, and to show how to use these general procedures in other subjects of study and in practice.
Graduates of this course should be able to:
• understand and use the basic terms from the combinatorics and probability theory;
• formulate questions that can be answered by the data and understand principles of collecting, processing and presentation of the data;
• select and use appropriate statistical methods for data analysis;
• propose and evaluate conclusions (inference) and make predictions using the data.
Teaching methods
Lectures
Tutorials
Summary
Combinatorics and probability. Random events, operations with them, sample space.
Definitions of events' probability - classical, geometrical, statistics. Conditional probability. Total probability and independent events.
Random variable and its characteristics.
Basic types of probability distributions of discrete random variables.
Basic types of probability distributions of continuous random variables.
Random vector, probability distribution, numerical characteristics.
Statistical file with one factor. Grouped frequency distribution.
Statistical file with two factors.
Regression and correlation.
Random sample, point and interval estimations of parameters.
Hypothesis testing.
Compulsory literature:
Radim Briš, Petra Škňouřilová. STATISTICS I. VŠB - Technical University of Ostrava, Ostrava 2007.
Recommended literature:
Way of continuous check of knowledge in the course of semester
Two tests, 3 projects - 1. regression, 2. characteristics of the statistical file, 3. statistical hypothesis testing
E-learning
Other requirements
There are no other requirements on students.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
1. Combinatorics
2. Introduction to probability theory
3. Conditional probability and independent phenomena. Bayes theorem. Complete probability theorem
4. Random variable and its characteristics
5.-7. Basic types of distribution of discrete and continuous random variables
8. Random vector
9. Statistical file with one argument
10. Statistical file with two arguments
11. Regression and correlation
12. Point and interval estimates of parameters
13. Testing hypotheses
14. Reserve - Examples.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
Předmět neobsahuje žádné hodnocení.