545-0154/02 – Applied statistics in mineral resources and mining industry (ASSP)

Gurantor departmentDepartment of Economics and Control SystemsCredits5
Subject guarantorRNDr. Radmila Sousedíková, Ph.D.Subject version guarantorRNDr. Radmila Sousedíková, Ph.D.
Study levelundergraduate or graduateRequirementCompulsory
Year2Semestersummer
Study languageEnglish
Year of introduction2019/2020Year of cancellation
Intended for the facultiesHGFIntended for study typesBachelor
Instruction secured by
LoginNameTuitorTeacher giving lectures
SOU70 RNDr. Radmila Sousedíková, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 2+2

Subject aims expressed by acquired skills and competences

Generating knowledge concerning elements and methods of statistical data processing, and applying the knowledge to analysis of statistical data on mineral resources and mining industry.

Teaching methods

Lectures
Tutorials

Summary

Subject concerns methods for describing univariate data sets, confidence intervals and tests of hypotheses, regression and correlation analysis, and time series analysis. Analyses are carried out on mineral resources and mining company data.

Compulsory literature:

MCCLAVE, James T., P. George BENSON and Terry SINCICH. Statistics for business and economics. Edition 13. Harlow: Pearson, 2018. ISBN 978-1-292-22708-5. Mineral Commodity summaries of the Czech Republic 2019. Czech Geological Survey. Available from: http://www.geology.cz/extranet-eng/publications/online/mineral-commodity-summaries/mineral%20-commodity-summaries-2019.pdf ANDERSON, David Ray, Dennis J. SWEENEY and Thomas Arthur WILLIAMS. Modern business statistics with Microsoft Office Excel. 5th ed. Stamford: Cengage Learning, 2015. ISBN 978-1-305-08218-2. ALWAN, Layth C., Bruce A. CRAIG and George P. MCCABE. The practice of statistics for business and economics. Fifth edition. New York: W. H. Freeman and Company, 2020. ISBN 978-1-319-32481-0.

Recommended literature:

SOUSEDÍKOVÁ, R. Business Statistics [CD-ROM]. Ostrava: VŠB-Technická univerzita Ostrava, 2015. 125 s. ISBN 978-80-248-3660-7. MC CLAVE, James T., George P. BENSON and Terry SINCICH. Statistics for Business and Economics. 12th ed. Upper Saddle River, New Jersey: Prentice Hall, 2014. ISBN 9781292023298. ANDERSON, David Ray. Statistics for business and economics. 12th ed., rev. Stamford: Cengage Learning, 2014. ISBN 978-1-285-84632-3. NEWBOLD, Paul, William Lee CARLSON and Betty THORNE. Statistics for business and economics. 8th ed., global ed. Harlow: Pearson Education, 2013. ISBN 978-0-273-76706-0.

Way of continuous check of knowledge in the course of semester

Regular feedback on the progress of knowledge during the current term is provided by semester projects. The course is completed by a written exam.

E-learning

The Moodle Learning Management System (lms.vsb.cz) is used for external communication of the teacher with students outside the class-room, as well as for communication among the students themselves.

Other requirements

There are no additional requirements.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

1.Basic statistical terms, statistical variable classification, classification of economic activities CZ-NACE 2.Methods of data collection, monthly statement of industry data Prům 1-12 3.Basic processing of statistical data: frequency distribution and class interval, application to frequency distribution of wages in mining company 4.Statistical plots – graphical representation of technical and production indicators of mining company 5.Quantiles, quartiles, deciles and centiles, basic processing of technical and production indicators of mining company 6.Measures of central tendency: means, median, mode, application to wages in mining company 7.Measures of variability: range, variance, standard deviation, variation coefficient, application to wages in mining company 8.Point and interval estimation, financial ratio estimation for mining company 9.Hypothesis testing, financial ratio testing for mining company 10.Regression analysis: regression function, estimation of regression function parameters, application to analysis of mining company cost 11.Correlation analysis: quality of regression function and intensity of dependency, application to analysis of mining company cost 12.Time series: basic characteristics of time series 13.Time series models, trend function, trend analysis of hard coal production

Conditions for subject completion

Full-time form (validity from: 2021/2022 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 30 (30) 17
                semestrální projekt Semestral project 30  17
        Examination Examination 70  34 3
Mandatory attendence participation: 80 % attendance

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Conditions for subject completion and attendance at the exercises within ISP: Consultation once a month, semester project, written exam

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Occurrence in study plans

Academic yearProgrammeBranch/spec.Spec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2024/2025 (B0724A290009) Mineral Economics P English Ostrava 2 Compulsory study plan
2023/2024 (B0724A290009) Mineral Economics P English Ostrava 2 Compulsory study plan
2022/2023 (B0724A290009) Mineral Economics P English Ostrava 2 Compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner
ECTS - FMG 2024/2025 Full-time English Optional 501 - Study Office stu. block
ECTS - FMG 2022/2023 Full-time English Optional 501 - Study Office stu. block
ECTS - FMG 2021/2022 Full-time English Optional 501 - Study Office stu. block

Assessment of instruction

Předmět neobsahuje žádné hodnocení.