541-0134/01 – Statistical Methods for Data Processing (SMTV)
Gurantor department | Department of Geological Engineering | Credits | 5 |
Subject guarantor | doc. RNDr. František Staněk, Ph.D. | Subject version guarantor | doc. RNDr. František Staněk, Ph.D. |
Study level | undergraduate or graduate | Requirement | Choice-compulsory |
Year | 3 | Semester | winter |
| | Study language | Czech |
Year of introduction | 2017/2018 | Year of cancellation | 2022/2023 |
Intended for the faculties | HGF | Intended for study types | Follow-up Master, Bachelor |
Subject aims expressed by acquired skills and competences
The aim of the course is to acquaint students with the basics of statistical analysis and essence of the methods of statistical data analysis. The main emphasis is on the issue of the use of traditional and non-parametric methods, their application and practical use. In this course, students will learn rigorous process and evaluate their experimental data. Students will be able to choose appropriate statistical methods, apply them to real data, evaluate and interpret results. An important part of the course is also to familiarize students how to work with statistical software.
Teaching methods
Lectures
Tutorials
Summary
The course deals with statistical analysis of experimental data and subsequent interpretations of the results. It provides basic information about the purpose, instruments and methods of statistical analysis. Introduces basic statistical terms, characteristics and relations between them and defines the methods of calculation. An emphasis is placed on the correct choice of methods for evaluating various types of experimental data and interpret results for use in practice. An integral part of the course is also a practical application of methods to real data in software environment for statistical computing (according to the current state of scientific field, for example - Statgraphics, SPSS, SAS, etc.), or in a spreadsheet, during exercises in the computer lab.
Compulsory literature:
Recommended literature:
Additional study materials
Way of continuous check of knowledge in the course of semester
Control questions, elaboration and submission of seminary work.
E-learning
Other requirements
Active participation (min. 70%) in seminars and successful completion of credit tests. The exam - oral with written preparation.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
1. Basic statistical terms
2. Set theory – cartesian product, relation, properties of relations
3. Random event and random variable
4. Descriptive and mathematical statistics
5. Exploratory data analysis – graphical techniques and statistical tests
6. Exploratory data analysis – outliers and data transformation
7. Basic statistical characteristics – classical and robust estimators of central tendency and variability
8. Estimators of central tendency and variability for small datasets
9. Interval estimation - confidence interval
10. The significance level
11. Parametric hypothesis tests
12. Nonparametric hypothesis tests
13. Interpolation, extrapolation, approximation
14. Linear regression and correlation analysis
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction