MB203 Continuous Models and Statistics B

Faculty of Informatics
Autumn 2019
Extent and Intensity
4/2/0. 6 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
doc. RNDr. Martin Čadek, CSc. (lecturer)
Mgr. Mária Šimková (seminar tutor)
doc. Mgr. Josef Šilhan, Ph.D. (alternate examiner)
Guaranteed by
prof. RNDr. Jan Slovák, DrSc.
Faculty of Informatics
Supplier department: Faculty of Science
Timetable
Mon 14:00–15:50 A217, Wed 14:00–15:50 A217
  • Timetable of Seminar Groups:
MB203/01: Mon 16:00–17:50 B204, M. Šimková
MB203/02: Tue 16:00–17:50 B204, M. Šimková
Prerequisites
! MB103 Cont. models and statistics && !NOW( MB103 Cont. models and statistics )
Recommended: knowledge of elementary functions, polynomials, rational functions. Further the elements of matrix calculus, as well knowledge of vector spaces and linear mappings and basic tools of Calculus in one real variable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 54 fields of study the course is directly associated with, display
Course objectives
At the end of this course, students should be able to:
use methods of calculus in the case of functions in more variables, inlcuding integration over curves and surfaces; solve basic optimization problems; exploit differential equations in continuous modeling;
understand theoretical concepts of the probability theory; apply methods of descriptive and mathematical statistics to basic problems.
Syllabus
  • The course is the third part of the four semester block of Mathematics. In the entire course, the fundamentals of algebra and number theory, linear algebra and analysis, numerical methods, combinatorics as well as probability and statistics are presented.
  • Calculus: differential and integral calculus in more variables, selected applications of Calculus, systems of differential equations, numerical solutions.
  • Elements of Probability, random variables and their characteristics, descriptive statistics, gentle introduction to methods of Mathematical Statistics.
Literature
    recommended literature
  • SLOVÁK, Jan, Martin PANÁK and Michal BULANT. Matematika drsně a svižně (Brisk Guide to Mathematics). 1st ed. Brno: Masarykova univerzita, 2013, 773 pp. ISBN 978-80-210-6307-5. Available from: https://dx.doi.org/10.5817/CZ.MUNI.O210-6308-2013. Základní učebnice matematiky pro vysokoškolské studium info
  • RILEY, K. F., M. P. HOBSON and S. J. BENCE. Mathematical methods for physics and engineering : a comprehensive guide. 2nd ed. Cambridge: Cambridge University Press, 2002, xxiii, 123. ISBN 0-521-81372-7. info
  • ZVÁRA, Karel and Josef ŠTĚPÁN. Pravděpodobnost a matematická statistika. 2. vyd. Praha: Matfyzpress, 2001, 230 s. ISBN 8085863243. info
  • DOŠLÁ, Zuzana and Ondřej DOŠLÝ. Diferenciální počet funkcí více proměnných. Vydání první. Brno: Vydavatelství Masarykovy univerzity, 1994, 130 stran. ISBN 8021009926. info
    not specified
  • PLCH, Roman, Zuzana DOŠLÁ and Petr SOJKA. Matematická analýza s programem Maple. Díl 1, Diferenciální počet funkcí více proměnných. (The Multivariable Calculus with program Maple. Part 1, Differencial calculus). prvni. Brno: Masarykova Universita, 1999, 80 pp. ISBN 80-210-2203-5. URL info
Teaching methods
There are theoretical lectures and standard tutorial accompanied by homework assessment.
Assessment methods
During the semester, two obligatory mid-term exams are evaluated (each for max 10 points). 5 minitests written during seminars are evaluated in total by max 5 points, 4 homeworks are evalueted by 4 points. The practical final exam is two hours long and written for max 20 points, followed by an oral exam checking theoretical understanding (10 points0. For successful examination (the grade at least E) the student needs in total 25 points or more and at least 5 points from the last written exam. More can be found in the IS for this course.
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018.

MB203 Continuous Models and Statistics B

Faculty of Informatics
Autumn 2018
Extent and Intensity
4/2/0. 6 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Jan Slovák, DrSc. (lecturer)
Mgr. Radek Suchánek, Ph.D. (seminar tutor)
doc. RNDr. Martin Čadek, CSc. (assistant)
doc. Mgr. Josef Šilhan, Ph.D. (assistant)
Guaranteed by
prof. RNDr. Jan Slovák, DrSc.
Faculty of Informatics
Supplier department: Faculty of Science
Timetable
Mon 17. 9. to Mon 10. 12. Mon 16:00–17:50 A320, Wed 8:00–9:50 A320
  • Timetable of Seminar Groups:
MB203/01: Wed 16:00–17:50 A320, R. Suchánek
Prerequisites
! MB103 Cont. models and statistics && !NOW( MB103 Cont. models and statistics )
Recommended: knowledge of elementary functions, polynomials, rational functions. Further the elements of matrix calculus, as well knowledge of vector spaces and linear mappings and basic tools of Calculus in one real variable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 17 fields of study the course is directly associated with, display
Course objectives
At the end of this course, students should be able to:
use methods of calculus in the case of functions in more variables, inlcuding integration over curves and surfaces; solve basic optimization problems; exploit differential equations in continuous modeling;
understand theoretical concepts of the probability theory; apply methods of descriptive and mathematical statistics to basic problems.
Syllabus
  • The course is the third part of the four semester block of Mathematics. In the entire course, the fundamentals of algebra and number theory, linear algebra and analysis, numerical methods, combinatorics as well as probability and statistics are presented.
  • Calculus: differential and integral calculus in more variables, selected applications of Calculus, systems of differential equations, numerical solutions.
  • Elements of Probability, random variables and their characteristics, descriptive statistics, gentle introduction to methods of Mathematical Statistics.
Literature
    recommended literature
  • SLOVÁK, Jan, Martin PANÁK and Michal BULANT. Matematika drsně a svižně (Brisk Guide to Mathematics). 1st ed. Brno: Masarykova univerzita, 2013, 773 pp. ISBN 978-80-210-6307-5. Available from: https://dx.doi.org/10.5817/CZ.MUNI.O210-6308-2013. Základní učebnice matematiky pro vysokoškolské studium info
  • RILEY, K. F., M. P. HOBSON and S. J. BENCE. Mathematical methods for physics and engineering : a comprehensive guide. 2nd ed. Cambridge: Cambridge University Press, 2002, xxiii, 123. ISBN 0-521-81372-7. info
  • ZVÁRA, Karel and Josef ŠTĚPÁN. Pravděpodobnost a matematická statistika. 2. vyd. Praha: Matfyzpress, 2001, 230 s. ISBN 8085863243. info
  • DOŠLÁ, Zuzana and Ondřej DOŠLÝ. Diferenciální počet funkcí více proměnných. Vydání první. Brno: Vydavatelství Masarykovy univerzity, 1994, 130 stran. ISBN 8021009926. info
    not specified
  • PLCH, Roman, Zuzana DOŠLÁ and Petr SOJKA. Matematická analýza s programem Maple. Díl 1, Diferenciální počet funkcí více proměnných. (The Multivariable Calculus with program Maple. Part 1, Differencial calculus). prvni. Brno: Masarykova Universita, 1999, 80 pp. ISBN 80-210-2203-5. URL info
Teaching methods
There are theoretical lectures and standard tutorial accompanied by homework assessment.
Assessment methods
During the semester, two obligatory mid-term exams are evaluated (each for max 10 points). The test written during seminars are evaluated in total by max 5 points. The practical final exam is two hours long and written for max 20 points, followed by an oral exam checking theoretical understanding. For successful examination (the grade at least E) the student needs in total 20 points or more.
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2019.

MB203 Continuous Models and Statistics B

Faculty of Informatics
Autumn 2017
Extent and Intensity
4/2/0. 6 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Jan Slovák, DrSc. (lecturer)
Mgr. Bc. Tomáš Janík (seminar tutor)
Mgr. Martin Panák, Ph.D. (seminar tutor)
Guaranteed by
prof. RNDr. Jan Slovák, DrSc.
Faculty of Informatics
Supplier department: Faculty of Science
Timetable
Mon 14:00–15:50 A218, Tue 16:00–17:50 B204
  • Timetable of Seminar Groups:
MB203/01: Wed 12:00–13:50 A320, M. Panák
Prerequisites
! MB103 Cont. models and statistics && !NOW( MB103 Cont. models and statistics )
Recommended: knowledge of elementary functions, polynomials, rational functions. Further the elements of matrix calculus, as well knowledge of vector spaces and linear mappings and basic tools of Calculus in one real variable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 17 fields of study the course is directly associated with, display
Course objectives
At the end of this course, students should be able to:
use methods of calculus in the case of functions in more variables, inlcuding integration over curves and surfaces; solve basic optimization problems; exploit differential equations in continuous modeling;
understand theoretical concepts of the probability theory; apply methods of descriptive and mathematical statistics to basic problems.
Syllabus
  • The course is the third part of the four semester block of Mathematics. In the entire course, the fundamentals of algebra and number theory, linear algebra and analysis, numerical methods, combinatorics as well as probability and statistics are presented.
  • Calculus: differential and integral calculus in more variables, selected applications of Calculus, systems of differential equations, numerical solutions.
  • Elements of Probability, random variables and their characteristics, descriptive statistics, gentle introduction to methods of Mathematical Statistics.
Literature
    recommended literature
  • SLOVÁK, Jan, Martin PANÁK and Michal BULANT. Matematika drsně a svižně (Brisk Guide to Mathematics). 1st ed. Brno: Masarykova univerzita, 2013, 773 pp. ISBN 978-80-210-6307-5. Available from: https://dx.doi.org/10.5817/CZ.MUNI.O210-6308-2013. Základní učebnice matematiky pro vysokoškolské studium info
  • RILEY, K. F., M. P. HOBSON and S. J. BENCE. Mathematical methods for physics and engineering : a comprehensive guide. 2nd ed. Cambridge: Cambridge University Press, 2002, xxiii, 123. ISBN 0-521-81372-7. info
  • ZVÁRA, Karel and Josef ŠTĚPÁN. Pravděpodobnost a matematická statistika. 2. vyd. Praha: Matfyzpress, 2001, 230 s. ISBN 8085863243. info
  • DOŠLÁ, Zuzana and Ondřej DOŠLÝ. Diferenciální počet funkcí více proměnných. Vydání první. Brno: Vydavatelství Masarykovy univerzity, 1994, 130 stran. ISBN 8021009926. info
    not specified
  • PLCH, Roman, Zuzana DOŠLÁ and Petr SOJKA. Matematická analýza s programem Maple. Díl 1, Diferenciální počet funkcí více proměnných. (The Multivariable Calculus with program Maple. Part 1, Differencial calculus). prvni. Brno: Masarykova Universita, 1999, 80 pp. ISBN 80-210-2203-5. URL info
Teaching methods
There are theoretical lectures and standard tutorial accompanied by homework assessment.
Assessment methods
During the semester, two obligatory mid-term exams are evaluated (each for max 10 points). The test written during seminars are evaluated in total by max 5 points. The practical final exam is two hours long and written for max 20 points, followed by an oral exam checking theoretical understanding. For successful examination (the grade at least E) the student needs in total 20 points or more.
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2018, Autumn 2019.

MB203 Continuous Models and Statistics B

Faculty of Informatics
Autumn 2016
Extent and Intensity
4/2. 6 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Jan Slovák, DrSc. (lecturer)
Mgr. Bc. Tomáš Janík (seminar tutor)
Mgr. Martin Panák, Ph.D. (seminar tutor)
Guaranteed by
prof. RNDr. Jan Slovák, DrSc.
Faculty of Informatics
Supplier department: Faculty of Informatics
Timetable
Mon 16:00–17:50 A218, Wed 10:00–11:50 A218
  • Timetable of Seminar Groups:
MB203/01: Wed 8:00–9:50 A320, M. Panák
Prerequisites
! MB103 Cont. models and statistics && !NOW( MB103 Cont. models and statistics )
Recommended: knowledge of elementary functions, polynomials, rational functions. Further the elements of matrix calculus, as well knowledge of vector spaces and linear mappings and basic tools of Calculus in one real variable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 17 fields of study the course is directly associated with, display
Course objectives
At the end of this course, students should be able to:
use methods of calculus in the case of functions in more variables, inlcuding integration over curves and surfaces; solve basic optimization problems; exploit differential equations in continuous modeling;
understand theoretical concepts of the probability theory; apply methods of descriptive and mathematical statistics to basic problems.
Syllabus
  • The course is the third part of the four semester block of Mathematics. In the entire course, the fundamentals of algebra and number theory, linear algebra and analysis, numerical methods, combinatorics as well as probability and statistics are presented.
  • Calculus: differential and integral calculus in more variables, selected applications of Calculus, systems of differential equations, numerical solutions.
  • Elements of Probability, random variables and their characteristics, descriptive statistics, gentle introduction to methods of Mathematical Statistics.
Literature
    recommended literature
  • SLOVÁK, Jan, Martin PANÁK and Michal BULANT. Matematika drsně a svižně (Brisk Guide to Mathematics). 1st ed. Brno: Masarykova univerzita, 2013, 773 pp. ISBN 978-80-210-6307-5. Available from: https://dx.doi.org/10.5817/CZ.MUNI.O210-6308-2013. Základní učebnice matematiky pro vysokoškolské studium info
  • RILEY, K. F., M. P. HOBSON and S. J. BENCE. Mathematical methods for physics and engineering : a comprehensive guide. 2nd ed. Cambridge: Cambridge University Press, 2002, xxiii, 123. ISBN 0-521-81372-7. info
  • ZVÁRA, Karel and Josef ŠTĚPÁN. Pravděpodobnost a matematická statistika. 2. vyd. Praha: Matfyzpress, 2001, 230 s. ISBN 8085863243. info
  • DOŠLÁ, Zuzana and Ondřej DOŠLÝ. Diferenciální počet funkcí více proměnných. Vydání první. Brno: Vydavatelství Masarykovy univerzity, 1994, 130 stran. ISBN 8021009926. info
    not specified
  • PLCH, Roman, Zuzana DOŠLÁ and Petr SOJKA. Matematická analýza s programem Maple. Díl 1, Diferenciální počet funkcí více proměnných. (The Multivariable Calculus with program Maple. Part 1, Differencial calculus). prvni. Brno: Masarykova Universita, 1999, 80 pp. ISBN 80-210-2203-5. URL info
Teaching methods
There are theoretical lectures and standard tutorial accompanied by homework assessment.
Assessment methods
During the semester, two obligatory mid-term exams are evaluated (each for max 10 points). The test written during seminars are evaluated in total by max 5 points. The practical final exam is two hours long and written for max 20 points, followed by an oral exam checking theoretical understanding. For successful examination (the grade at least E) the student needs in total 20 points or more.
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2017, Autumn 2018, Autumn 2019.

MB203 Continuous Models and Statistics B

Faculty of Informatics
Autumn 2015
Extent and Intensity
4/2. 6 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Jan Slovák, DrSc. (lecturer)
Mgr. Bc. Tomáš Janík (seminar tutor)
Mgr. Martin Panák, Ph.D. (seminar tutor)
Guaranteed by
prof. RNDr. Jan Slovák, DrSc.
Faculty of Informatics
Supplier department: Faculty of Informatics
Timetable
Mon 16:00–17:50 A320, Tue 16:00–17:50 A320
  • Timetable of Seminar Groups:
MB203/T02: Tue 22. 9. to Tue 22. 12. Tue 10:00–11:35 116, T. Janík, Nepřihlašuje se. Určeno pro studenty se zdravotním postižením.
MB203/01: Tue 14:00–15:50 B204, M. Panák
Prerequisites
! MB103 Cont. models and statistics && !NOW( MB103 Cont. models and statistics )
Recommended: knowledge of elementary functions, polynomials, rational functions. Further the elements of matrix calculus, as well knowledge of vector spaces and linear mappings and basic tools of Calculus in one real variable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 17 fields of study the course is directly associated with, display
Course objectives
At the end of this course, students should be able to:
use methods of calculus in the case of functions in more variables, inlcuding integration over curves and surfaces; solve basic optimization problems; exploit differential equations in continuous modeling;
understand theoretical concepts of the probability theory; apply methods of descriptive and mathematical statistics to basic problems.
Syllabus
  • The course is the third part of the four semester block of Mathematics. In the entire course, the fundamentals of algebra and number theory, linear algebra and analysis, numerical methods, combinatorics as well as probability and statistics are presented.
  • Calculus: differential and integral calculus in more variables, selected applications of Calculus, systems of differential equations, numerical solutions.
  • Elements of Probability, random variables and their characteristics, descriptive statistics, gentle introduction to methods of Mathematical Statistics.
Literature
    recommended literature
  • SLOVÁK, Jan, Martin PANÁK and Michal BULANT. Matematika drsně a svižně (Brisk Guide to Mathematics). 1st ed. Brno: Masarykova univerzita, 2013, 773 pp. ISBN 978-80-210-6307-5. Available from: https://dx.doi.org/10.5817/CZ.MUNI.O210-6308-2013. Základní učebnice matematiky pro vysokoškolské studium info
  • RILEY, K. F., M. P. HOBSON and S. J. BENCE. Mathematical methods for physics and engineering : a comprehensive guide. 2nd ed. Cambridge: Cambridge University Press, 2002, xxiii, 123. ISBN 0-521-81372-7. info
  • ZVÁRA, Karel and Josef ŠTĚPÁN. Pravděpodobnost a matematická statistika. 2. vyd. Praha: Matfyzpress, 2001, 230 s. ISBN 8085863243. info
  • DOŠLÁ, Zuzana and Ondřej DOŠLÝ. Diferenciální počet funkcí více proměnných. Vydání první. Brno: Vydavatelství Masarykovy univerzity, 1994, 130 stran. ISBN 8021009926. info
    not specified
  • PLCH, Roman, Zuzana DOŠLÁ and Petr SOJKA. Matematická analýza s programem Maple. Díl 1, Diferenciální počet funkcí více proměnných. (The Multivariable Calculus with program Maple. Part 1, Differencial calculus). prvni. Brno: Masarykova Universita, 1999, 80 pp. ISBN 80-210-2203-5. URL info
Teaching methods
There are theoretical lectures and standard tutorial accompanied by homework assessment.
Assessment methods
During the semester, two obligatory mid-term exams are evaluated (each for max 10 points). The test written during seminars are evaluated in total by max 5 points. The practical final exam is two hours long and written for max 20 points, followed by an oral exam checking theoretical understanding. For successful examination (the grade at least E) the student needs in total 20 points or more.
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2013, Autumn 2014, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019.

MB203 Continuous Models and Statistics B

Faculty of Informatics
Autumn 2014
Extent and Intensity
4/2. 6 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Jan Slovák, DrSc. (lecturer)
Mgr. Martin Panák, Ph.D. (seminar tutor)
Guaranteed by
prof. RNDr. Jan Slovák, DrSc.
Faculty of Informatics
Supplier department: Faculty of Informatics
Timetable
Mon 18:00–19:50 A217, Tue 14:00–15:50 A318
  • Timetable of Seminar Groups:
MB203/01: Tue 8:00–9:50 B204, M. Panák
Prerequisites
! MB103 Cont. models and statistics && !NOW( MB103 Cont. models and statistics )
Recommended: knowledge of elementary functions, polynomials, rational functions. Further the elements of matrix calculus, as well knowledge of vector spaces and linear mappings and basic tools of Calculus in one real variable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 17 fields of study the course is directly associated with, display
Course objectives
At the end of this course, students should be able to:
use methods of calculus in the case of functions in more variables, inlcuding integration over curves and surfaces; solve basic optimization problems; exploit differential equations in continuous modeling;
understand theoretical concepts of the probability theory; apply methods of descriptive and mathematical statistics to basic problems.
Syllabus
  • The course is the third part of the four semester block of Mathematics. In the entire course, the fundamentals of algebra and number theory, linear algebra and analysis, numerical methods, combinatorics as well as probability and statistics are presented.
  • Calculus: differential and integral calculus in more variables, selected applications of Calculus, systems of differential equations, numerical solutions.
  • Elements of Probability, random variables and their characteristics, descriptive statistics, gentle introduction to methods of Mathematical Statistics.
Literature
    recommended literature
  • SLOVÁK, Jan, Martin PANÁK and Michal BULANT. Matematika drsně a svižně (Brisk Guide to Mathematics). 1st ed. Brno: Masarykova univerzita, 2013, 773 pp. ISBN 978-80-210-6307-5. Available from: https://dx.doi.org/10.5817/CZ.MUNI.O210-6308-2013. Základní učebnice matematiky pro vysokoškolské studium info
  • RILEY, K. F., M. P. HOBSON and S. J. BENCE. Mathematical methods for physics and engineering : a comprehensive guide. 2nd ed. Cambridge: Cambridge University Press, 2002, xxiii, 123. ISBN 0-521-81372-7. info
  • ZVÁRA, Karel and Josef ŠTĚPÁN. Pravděpodobnost a matematická statistika. 2. vyd. Praha: Matfyzpress, 2001, 230 s. ISBN 8085863243. info
  • DOŠLÁ, Zuzana and Ondřej DOŠLÝ. Diferenciální počet funkcí více proměnných. Vydání první. Brno: Vydavatelství Masarykovy univerzity, 1994, 130 stran. ISBN 8021009926. info
    not specified
  • PLCH, Roman, Zuzana DOŠLÁ and Petr SOJKA. Matematická analýza s programem Maple. Díl 1, Diferenciální počet funkcí více proměnných. (The Multivariable Calculus with program Maple. Part 1, Differencial calculus). prvni. Brno: Masarykova Universita, 1999, 80 pp. ISBN 80-210-2203-5. URL info
Teaching methods
There are theoretical lectures and standard tutorial accompanied by homework assessment.
Assessment methods
During the semester, two obligatory mid-term exams are evaluated (each for max 10 points). The test written during seminars are evaluated in total by max 5 points. The practical final exam is two hours long and written for max 20 points, followed by an oral exam checking theoretical understanding. For successful examination (the grade at least E) the student needs in total 20 points or more.
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2013, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019.

MB203 Continuous Models and Statistics B

Faculty of Informatics
Autumn 2013
Extent and Intensity
4/2. 6 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Jan Slovák, DrSc. (lecturer)
Mgr. Michal Bulant, Ph.D. (lecturer)
Mgr. Martin Panák, Ph.D. (seminar tutor)
Guaranteed by
prof. RNDr. Jan Slovák, DrSc.
Faculty of Informatics
Supplier department: Faculty of Informatics
Timetable
Tue 16:00–17:50 G125, Wed 16:00–17:50 G125
  • Timetable of Seminar Groups:
MB203/01: Wed 14:00–15:50 G125, M. Panák
MB203/02: Fri 8:00–9:50 G124, M. Panák
Prerequisites
! MB103 Cont. models and statistics && !NOW( MB103 Cont. models and statistics )
Recommended: knowledge of elementary functions, polynomials, rational functions. Further the elements of matrix calculus, as well knowledge of vector spaces and linear mappings and basic tools of Calculus in one real variable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 17 fields of study the course is directly associated with, display
Course objectives
At the end of this course, students should be able to:
use methods of calculus in the case of functions in more variables, inlcuding integration over curves and surfaces; solve basic optimization problems; exploit differential equations in continuous modeling;
understand theoretical concepts of the probability theory; apply methods of descriptive and mathematical statistics to basic problems.
Syllabus
  • The course is the third part of the four semester block of Mathematics. In the entire course, the fundamentals of algebra and number theory, linear algebra and analysis, numerical methods, combinatorics as well as probability and statistics are presented.
  • Calculus: differential and integral calculus in more variables, selected applications of Calculus, systems of differential equations, numerical solutions.
  • Elements of Probability, random variables and their characteristics, descriptive statistics, gentle introduction to methods of Mathematical Statistics.
Literature
    recommended literature
  • SLOVÁK, Jan, Martin PANÁK and Michal BULANT. Matematika drsně a svižně (Brisk Guide to Mathematics). 1st ed. Brno: Masarykova univerzita, 2013, 773 pp. ISBN 978-80-210-6307-5. Available from: https://dx.doi.org/10.5817/CZ.MUNI.O210-6308-2013. Základní učebnice matematiky pro vysokoškolské studium info
  • RILEY, K. F., M. P. HOBSON and S. J. BENCE. Mathematical methods for physics and engineering : a comprehensive guide. 2nd ed. Cambridge: Cambridge University Press, 2002, xxiii, 123. ISBN 0-521-81372-7. info
  • ZVÁRA, Karel and Josef ŠTĚPÁN. Pravděpodobnost a matematická statistika. 2. vyd. Praha: Matfyzpress, 2001, 230 s. ISBN 8085863243. info
  • DOŠLÁ, Zuzana and Ondřej DOŠLÝ. Diferenciální počet funkcí více proměnných. Vydání první. Brno: Vydavatelství Masarykovy univerzity, 1994, 130 stran. ISBN 8021009926. info
    not specified
  • PLCH, Roman, Zuzana DOŠLÁ and Petr SOJKA. Matematická analýza s programem Maple. Díl 1, Diferenciální počet funkcí více proměnných. (The Multivariable Calculus with program Maple. Part 1, Differencial calculus). prvni. Brno: Masarykova Universita, 1999, 80 pp. ISBN 80-210-2203-5. URL info
Teaching methods
There are theoretical lectures and standard tutorial accompanied by homework assessment.
Assessment methods
During the semester, two obligatory mid-term exams are evaluated (each for max 10 points). The test written during seminars are evaluated in total by max 5 points. The practical final exam is two hours long and written for max 20 points, followed by an oral exam checking theoretical understanding. For successful examination (the grade at least E) the student needs in total 20 points or more.
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019.

MB203 Continuous Models and Statistics B

Faculty of Informatics
Autumn 2021

The course is not taught in Autumn 2021

Extent and Intensity
4/2/0. 6 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
doc. RNDr. Martin Čadek, CSc. (lecturer)
Mgr. Mária Šimková (seminar tutor)
doc. Mgr. Josef Šilhan, Ph.D. (alternate examiner)
Guaranteed by
prof. RNDr. Jan Slovák, DrSc.
Faculty of Informatics
Supplier department: Faculty of Science
Prerequisites
! MB103 Cont. models and statistics && !NOW( MB103 Cont. models and statistics )
Recommended: knowledge of elementary functions, polynomials, rational functions. Further the elements of matrix calculus, as well knowledge of vector spaces and linear mappings and basic tools of Calculus in one real variable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 54 fields of study the course is directly associated with, display
Course objectives
At the end of this course, students should be able to:
use methods of calculus in the case of functions in more variables, inlcuding integration over curves and surfaces; solve basic optimization problems; exploit differential equations in continuous modeling;
understand theoretical concepts of the probability theory; apply methods of descriptive and mathematical statistics to basic problems.
Syllabus
  • The course is the third part of the four semester block of Mathematics. In the entire course, the fundamentals of algebra and number theory, linear algebra and analysis, numerical methods, combinatorics as well as probability and statistics are presented.
  • Calculus: differential and integral calculus in more variables, selected applications of Calculus, systems of differential equations, numerical solutions.
  • Elements of Probability, random variables and their characteristics, descriptive statistics, gentle introduction to methods of Mathematical Statistics.
Literature
    recommended literature
  • SLOVÁK, Jan, Martin PANÁK and Michal BULANT. Matematika drsně a svižně (Brisk Guide to Mathematics). 1st ed. Brno: Masarykova univerzita, 2013, 773 pp. ISBN 978-80-210-6307-5. Available from: https://dx.doi.org/10.5817/CZ.MUNI.O210-6308-2013. Základní učebnice matematiky pro vysokoškolské studium info
  • RILEY, K. F., M. P. HOBSON and S. J. BENCE. Mathematical methods for physics and engineering : a comprehensive guide. 2nd ed. Cambridge: Cambridge University Press, 2002, xxiii, 123. ISBN 0-521-81372-7. info
  • ZVÁRA, Karel and Josef ŠTĚPÁN. Pravděpodobnost a matematická statistika. 2. vyd. Praha: Matfyzpress, 2001, 230 s. ISBN 8085863243. info
  • DOŠLÁ, Zuzana and Ondřej DOŠLÝ. Diferenciální počet funkcí více proměnných. Vydání první. Brno: Vydavatelství Masarykovy univerzity, 1994, 130 stran. ISBN 8021009926. info
    not specified
  • PLCH, Roman, Zuzana DOŠLÁ and Petr SOJKA. Matematická analýza s programem Maple. Díl 1, Diferenciální počet funkcí více proměnných. (The Multivariable Calculus with program Maple. Part 1, Differencial calculus). prvni. Brno: Masarykova Universita, 1999, 80 pp. ISBN 80-210-2203-5. URL info
Teaching methods
There are theoretical lectures and standard tutorial accompanied by homework assessment.
Assessment methods
During the semester, two obligatory mid-term exams are evaluated (each for max 10 points). 5 minitests written during seminars are evaluated in total by max 5 points, 4 homeworks are evalueted by 4 points. The practical final exam is two hours long and written for max 20 points, followed by an oral exam checking theoretical understanding (10 points0. For successful examination (the grade at least E) the student needs in total 25 points or more and at least 5 points from the last written exam. More can be found in the IS for this course.
Language of instruction
Czech
Further comments (probably available only in Czech)
The course is taught annually.
The course is taught: every week.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019.

MB203 Continuous Models and Statistics B

Faculty of Informatics
Autumn 2020

The course is not taught in Autumn 2020

Extent and Intensity
4/2/0. 6 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
doc. RNDr. Martin Čadek, CSc. (lecturer)
Mgr. Mária Šimková (seminar tutor)
doc. Mgr. Josef Šilhan, Ph.D. (alternate examiner)
Guaranteed by
prof. RNDr. Jan Slovák, DrSc.
Faculty of Informatics
Supplier department: Faculty of Science
Prerequisites
! MB103 Cont. models and statistics && !NOW( MB103 Cont. models and statistics )
Recommended: knowledge of elementary functions, polynomials, rational functions. Further the elements of matrix calculus, as well knowledge of vector spaces and linear mappings and basic tools of Calculus in one real variable.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 54 fields of study the course is directly associated with, display
Course objectives
At the end of this course, students should be able to:
use methods of calculus in the case of functions in more variables, inlcuding integration over curves and surfaces; solve basic optimization problems; exploit differential equations in continuous modeling;
understand theoretical concepts of the probability theory; apply methods of descriptive and mathematical statistics to basic problems.
Syllabus
  • The course is the third part of the four semester block of Mathematics. In the entire course, the fundamentals of algebra and number theory, linear algebra and analysis, numerical methods, combinatorics as well as probability and statistics are presented.
  • Calculus: differential and integral calculus in more variables, selected applications of Calculus, systems of differential equations, numerical solutions.
  • Elements of Probability, random variables and their characteristics, descriptive statistics, gentle introduction to methods of Mathematical Statistics.
Literature
    recommended literature
  • SLOVÁK, Jan, Martin PANÁK and Michal BULANT. Matematika drsně a svižně (Brisk Guide to Mathematics). 1st ed. Brno: Masarykova univerzita, 2013, 773 pp. ISBN 978-80-210-6307-5. Available from: https://dx.doi.org/10.5817/CZ.MUNI.O210-6308-2013. Základní učebnice matematiky pro vysokoškolské studium info
  • RILEY, K. F., M. P. HOBSON and S. J. BENCE. Mathematical methods for physics and engineering : a comprehensive guide. 2nd ed. Cambridge: Cambridge University Press, 2002, xxiii, 123. ISBN 0-521-81372-7. info
  • ZVÁRA, Karel and Josef ŠTĚPÁN. Pravděpodobnost a matematická statistika. 2. vyd. Praha: Matfyzpress, 2001, 230 s. ISBN 8085863243. info
  • DOŠLÁ, Zuzana and Ondřej DOŠLÝ. Diferenciální počet funkcí více proměnných. Vydání první. Brno: Vydavatelství Masarykovy univerzity, 1994, 130 stran. ISBN 8021009926. info
    not specified
  • PLCH, Roman, Zuzana DOŠLÁ and Petr SOJKA. Matematická analýza s programem Maple. Díl 1, Diferenciální počet funkcí více proměnných. (The Multivariable Calculus with program Maple. Part 1, Differencial calculus). prvni. Brno: Masarykova Universita, 1999, 80 pp. ISBN 80-210-2203-5. URL info
Teaching methods
There are theoretical lectures and standard tutorial accompanied by homework assessment.
Assessment methods
During the semester, two obligatory mid-term exams are evaluated (each for max 10 points). 5 minitests written during seminars are evaluated in total by max 5 points, 4 homeworks are evalueted by 4 points. The practical final exam is two hours long and written for max 20 points, followed by an oral exam checking theoretical understanding (10 points0. For successful examination (the grade at least E) the student needs in total 25 points or more and at least 5 points from the last written exam. More can be found in the IS for this course.
Language of instruction
Czech
Further comments (probably available only in Czech)
The course is taught annually.
The course is taught: every week.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019.

MB203 Continuous Models and Statistics B

Faculty of Informatics
Autumn 2012

The course is not taught in Autumn 2012

Extent and Intensity
4/2. 6 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
Mgr. Michal Bulant, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Jan Slovák, DrSc.
Faculty of Informatics
Supplier department: Faculty of Informatics
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 17 fields of study the course is directly associated with, display
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is taught: every week.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, Autumn 2018, Autumn 2019.
  • Enrolment Statistics (recent)