541-0181/01 – Statistics (ST)

Gurantor departmentDepartment of Geological EngineeringCredits4
Subject guarantorMgr. Oldřich Motyka, Ph.D.Subject version guarantorMgr. Oldřich Motyka, Ph.D.
Study levelundergraduate or graduateRequirementCompulsory
Year1Semestersummer
Study languageCzech
Year of introduction2018/2019Year of cancellation
Intended for the facultiesHGFIntended for study typesFollow-up Master, Bachelor
Instruction secured by
LoginNameTuitorTeacher giving lectures
STA22 doc. RNDr. František Staněk, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 2+2
Part-time Credit and Examination 8+8

Subject aims expressed by acquired skills and competences

This course is dedicated to finding solutions of probabilistic and statistical problems. These problems can arise from other courses as well as from practice. The main emphasis lays in explanation of fundamental principles of probabilistic and statistical methods and of their general properties. The students learn how to decide which procedure is a suitable tool for solving a specific problem. The first part of the course deals with basic probabilistic notions and with the way in which to understand these notions from both theoretical and practical points of view. In the second part of the course the students learn the statistical way of thinking as a mean of understanding real-life processes. The basic methods of collecting and analysing statistical data are introduced. The students are taught how to use these general methods to solve the problems arising from other courses of their study and from practice. The students learn how to use existing software specialized for statistical computations, too.

Teaching methods

Lectures
Tutorials

Summary

The introductory course Applied Statistics deals with the basic problems of probability and statistics. It gives the base for ability to describe random processes by means of random variable and random vector. The course deals with the basic problems of descriptive statistics, methods of statistical inference, tests of hypotheses and regression and correlation analysis for one- or multi-dimensional statistical set of data.

Compulsory literature:

Briš, R. PROBABILITY AND STATISTICS FOR ENGINEERS, Ostrava, VŠB - TU, 2011 (http://homel.vsb.cz/~bri10/). Mann, P. S. Introductory Statistics. Wiley, 2010. Montgomery, D. C. Applied Statistics and Probability for Engineers. Wiley, 2003. Hodges, J. L., Lehmann, E. L. Basic Concepts of Probability and Statistics. SIAM, 2005.

Recommended literature:

Barnett, V. Environmental Statistics. Methods and Applications. Wiley, 2003. Hammer, R, Harper, D. Paleontological Data Analysis. Malden, MA: Blackwell Pub, 2006. Meier, P. C., Zünd, R., E. Statistical Methods in Analytical Chemistry. Wiley, 2000. Benjamin, J. R., Cornell, C. A. Probability, Statistics, and Decision for Civil Engineers. Dover Publications, 2014.

Additional study materials

Way of continuous check of knowledge in the course of semester

Successful completion of written tests and defense of assigned programs.

E-learning

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Other requirements

Active participation in seminars and successful completion of written tests.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

1. Combinatorics. Random experiment. Random event. Random event operations. Disjoint events. Sample space. 2. Definition of probability - axiomatic, classical, geometrical, statistical. 3. Conditional probability. Total probability. Bayes' theorem. Repeated attempts. 4. Random variable, discrete random variable, continuous random variable. Probability mass function, probability density function, cumulative distribution function. 5. Characteristics of random variables. 6. Basic types of probability distribution of discrete random variable. Basic types of probability distribution of continuous random variable. 7. Random vector, probability distribution, numerical characteristics. 8. Mathematic statistics. Statistical characteristics. Exploratory data analysis. 9. Population, random sampling, sample characteristics. 10. Point and interval estimation. 11. Hypothesis testing. Parametric tests. Nonparametric tests. 12. Verifying the type of statistical distribution. Transform into normal distribution. 13. Two-dimensional statistical file. Regression and correlation analysis.

Conditions for subject completion

Full-time form (validity from: 2018/2019 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)		Min. number of pointsMax. počet pokusů
Credit and Examination Credit and Examination 100 (100) 51
        Credit Credit 33  17
        Examination Examination 67  18 3
Mandatory attendence participation: Attendance at seminars is mandatory, the maximum excused absence is 20%.

Show history

Conditions for subject completion and attendance at the exercises within ISP: Conditions for passing the course Credit: - Successful completion of two tests during the semester. - Elaboration and defense of assigned programs. Exam: - Successful completion of the written part of the exam. - Answering the given additional questions according to the published list of questions. Participation in exercises: To the maximum extent possible (at least for writing tests and getting to know the assignments of the programs). Others in the form of individual consultations.

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Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner

Assessment of instruction



2021/2022 Summer
2020/2021 Summer
2020/2021 Winter
2019/2020 Summer
2018/2019 Summer