470-2401/04 – Statistics I (STA1)

Gurantor departmentDepartment of Applied MathematicsCredits6
Subject guarantorprof. Ing. Radim Briš, CSc.Subject version guarantorprof. Ing. Radim Briš, CSc.
Study levelundergraduate or graduateRequirementCompulsory
Year2Semestersummer
Study languageEnglish
Year of introduction2019/2020Year of cancellation
Intended for the facultiesFEIIntended for study typesBachelor
Instruction secured by
LoginNameTuitorTeacher giving lectures
BRI10 prof. Ing. Radim Briš, CSc.
KRA0220 Ing. Jan Kracík, 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 10+10

Subject aims expressed by acquired skills and competences

Studens learn basics of mathematical theory of statistics and gain hands-on experince with data analysis using software environment R.

Teaching methods

Lectures
Tutorials
Project work

Summary

The course is an introduction to mathematical statistics. Students learn mathematical basis of statistics and gain hands-on experince with data analysis using software environment R.

Compulsory literature:

RAO, C. RADHAKRISHNA. Linear statistical inference and its applications. 2. ed., paperback ed. New York: Wiley, 2002. ISBN 0471218758. Briš R., Probability and Statistics for Engineers, 2011, electronics script, Project CZ.1.07/2.2.00/15.0132. Dostupné z http://homel.vsb.cz/~bri10/Teaching/Prob%20&%20Stat.pdf TEETOR, Paul. R cookbook. Sebastopol, CA: O'Reilly, 2011. ISBN 9780596809157

Recommended literature:

STERNSTEIN, Martin. Barron's AP statistics. 5th ed. Hauppauge, N.Y.: Barron's Educational Series, c2010. ISBN 978-0-7641-4089-1.

Way of continuous check of knowledge in the course of semester

2 tests per 10 points during the semester semestral project with max. 20 points Conditions for the credit: project handed in and total score at least 20 points

E-learning

Other requirements

There are not defined other requirements for student.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

Lectures: Random sample - Probability distributions of quadratic forms - Random sample from normal distribution - Confidence intervals for parameters of a normal distribution Hypothesis testing - Simple hypothesis - Simple null hypothesis and Composite alternative hypothesis Estimation theory - Point estimates and their properties - Sufficient statistics - Maximum likelihood estimation, method of moments Analysis of variance - One-way analysis of variance Regression analysis - Linear regression Excersises follow lectures.

Conditions for subject completion

Full-time form (validity from: 2019/2020 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 40  20
        Examination Examination 60  20 3
Mandatory attendence participation: Participation at all exercises is obligatory, 2 apologies are accepted. Participation at lectures is recommended, knowledge of lecture materials is a prerequisite for participation at the exercises.

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Conditions for subject completion and attendance at the exercises within ISP: Completion of all mandatory tasks within individually agreed deadlines.

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Occurrence in study plans

Academic yearProgrammeBranch/spec.Spec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2023/2024 (B0541A170009) Computational and Applied Mathematics VMI P English Ostrava 2 Compulsory study plan
2022/2023 (B0541A170009) Computational and Applied Mathematics VMI P English Ostrava 2 Compulsory study plan
2021/2022 (B0541A170009) Computational and Applied Mathematics VMI P English Ostrava 2 Compulsory study plan
2020/2021 (B0541A170009) Computational and Applied Mathematics VMI P English Ostrava 2 Compulsory study plan
2019/2020 (B0541A170009) Computational and Applied Mathematics VMI P English Ostrava 2 Compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner

Assessment of instruction

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