Higher Mathematics II
BASIC DATA
course listing
A - main register
course code
VAY0790
course title in Estonian
Kõrgem matemaatika II
course title in English
Higher Mathematics II
course volume CP
-
ECTS credits
3.00
to be declared
yes
fully online course
not
assessment form
Examination
teaching semester
spring
language of instruction
Estonian
English
Prerequisite(s)
Prerequisite 1
Higher Mathematics (VAY0810)
Study programmes that contain the course
code of the study programme version
course compulsory
VDLR14/25
yes
VDXR17/25
yes
Structural units teaching the course
V - Estonian Maritime Academy
Course description link
Timetable link
View the timetable
Version:
VERSION SPECIFIC DATA
course aims in Estonian
Aine eesmärk on:
- tutvustada tõenäosusteooria põhilisi mõisteid ja meetodeid;
- süvendada teadmisi juhuslikkusest;
- anda oskusi juhuslikkuses peituvate seaduspärasuste kirjeldamiseks statistika meetodite abil;
- süvendada teadmisi ja oskusi andmetöötluses;
- esitada arv- ja funktsionaalridade põhiprobleemide praktilised rakendused;
- õpetada lahendama mainitud teooriaga seotud põhilisi ülesandeid;
- harjutada üliõpilasi matemaatilise mõtlemise ja sümboolikaga.
course aims in English
The aim of this course is to:
- give an overview of the main methods stemming from the theory of probability;
- deepen the knowledge about randomness;
- give knowledge about the laws of random phenomena and ability to indentify them by means of methods of statistics;
- deepen knowledge and skills for data processing;
- give knowledge about the theory of functional series and their applications;
- teach to solve main problems of the theory mentioned above;
- make the students accustomed with the mathematical thinking and symbolism.
learning outcomes in the course in Est.
Õppeaine läbinud üliõpilane:
- tunneb tõenäosusteooria põhimõisteid, oskab leida sündmuste summa ja korrutise tõenäosust ning kasutada täistõenäosuse, Bayesi ja Bernoulli valemeid ülesannete lahendamisel;
- tunneb juhusliku suuruse, selle jaotusfunktsiooni, jaotustiheduse, karakteristliku funktsiooni, genereeriva funktsiooni ja põhiliste arvkarakteristikute mõisteid ning oskab lahendada ülesandeid enamlevinud jaotuste parameetrite määramise ja nendega seotud tõenäosuste arvutamise kohta;
- tunneb juhusliku vektori, selle jaotusfunktsiooni, jaotustiheduse mõisteid ning oskab lahendada vastavaid ülesandeid;
- tunneb matemaatilise statistika põhimõisteid, oskab leida punkt- ja vahemikhinnanguid;
- oskab kasutada MS Exceli korrelatsioon- ja regressioonananlüüsi vahendeid nähtustevaheliste seoste uurimiseks ja kirjeldamiseks;
- uurib astmeridade koonduvust, arendab funktsiooni astmeritta ja kasutab astmeridu rakendustes;
- arendab funktsiooni Fourier' ritta, leiab funktsiooni Fourier' teisendust ning kasutab Fourier' ridu ja Fourier' teisendusi;
- testib praktiliste ülesannete lahendamisel saadud tulemuste õigsust.
learning outcomes in the course in Eng.
After completing this course the student:
- knows the main concepts of the theory of probability, is able to find probabilities of sums and products of events and use the formula of total probability and Bayes and Bernoulli formulas to solve problems;
- knows the concepts of the random variable, distribution function, density function, characteristic function, generating function and main numerical characteristics and is able to solve problems to find parameters of distributions and to compute related probabilities;
- knows the concepts of event, its distribution function, density and is able to solve related problems;
- knows of main concepts of the mathematical statistics, is able to find point and interval estimators;
- is able to use MS Excel tools of correlation and regression analysis and describe linear relationships between variables;
- is able to investigate the convergence of functional series;
- is able to find Fourier-series expansions, Fourier transforms of function and to apply Fourier series and transforms;
- is able to check the correctness of results obtained by solution of practical exercises.
brief description of the course in Estonian
Tõenäosusteooria põhimõisted ja seosed. Juhuslik suurus. Jaotusfunktsioonid. Juhuslikud protsessid. Matemaatilise statistika põhimõisted. Akvakarakteristikud ja vahemikuhinnangud. Dispersioon, korrelatsioon, regressioon. Ms Exceli vahendid andmete töötlemiseks. Astmeread. Fourier' rida. Taylori rida. Fourier' teisendus. Matemaatika tarkvara
brief description of the course in English
Main concepts of the theory of probability. Random variable. Distribution function. Main concepts of the mathematical statistics. Numerical characteristics. Confidence intervals for parameters. Dispersion. Regression. Correlation.
Computer statistics. Power series. Fourier' series. Taylor’ series. Fourier' transforms. Mathematical software.
type of assessment in Estonian
.
type of assessment in English
.
independent study in Estonian
4 kodutööd, kus tuleb lahendada harjutustundides lahendatud ülesannetega sarnaseid ülesandeid. Ettevalmistus kontrolltöödeks ja eksamiks.
independent study in English
4 homeworks based on problems that are solved in practical lessons and preparation for written tests and examination.
study literature
.
study forms and load
daytime study: weekly hours
2.0
session-based study work load (in a semester):
lectures
0.0
lectures
-
practices
0.0
practices
-
exercises
2.0
exercises
-
lecturer in charge
-
LECTURER SYLLABUS INFO
semester of studies
teaching lecturer / unit
language of instruction
Extended syllabus
2024/2025 spring
Julia Tammela, V - Estonian Maritime Academy
Estonian
    VAY0790 Assessment method.pdf 
    display more
    2024/2025 autumn
    Julia Tammela, V - Estonian Maritime Academy
    Estonian
      VAY0790 Assessment method.pdf 
      2023/2024 spring
      Julia Tammela, V - Estonian Maritime Academy
      Estonian
        2023/2024 autumn
        Julia Tammela, V - Estonian Maritime Academy
        Estonian
          2022/2023 spring
          Julia Tammela, V - Estonian Maritime Academy
          Estonian
            2022/2023 autumn
            Julia Tammela, V - Estonian Maritime Academy
            Estonian
              2021/2022 spring
              Julia Tammela, V - Estonian Maritime Academy
              Estonian
                VAY0790 Assessment method.pdf 
                2021/2022 autumn
                Julia Tammela, V - Estonian Maritime Academy
                Estonian
                  VAY0790 Assessment method.pdf 
                  2020/2021 spring
                  Julia Tammela, V - Estonian Maritime Academy
                  Estonian
                    VAY0790 Assessment method.pdf 
                    2020/2021 autumn
                    Julia Tammela, V - Estonian Maritime Academy
                    Estonian
                      VAY0790 Assessment method.pdf 
                      2019/2020 spring
                      Julia Tammela, V - Estonian Maritime Academy
                      Estonian
                        VAY0790 Assessment method.pdf 
                        2019/2020 autumn
                        Julia Tammela, V - Estonian Maritime Academy
                        Estonian
                          VAY0790 Assessment method.pdf 
                          2018/2019 spring
                          Julia Tammela, V - Estonian Maritime Academy
                          Estonian
                            VAY0790 Assessment method.pdf 
                            2018/2019 autumn
                            Julia Tammela, V - Estonian Maritime Academy
                            Estonian
                              VAY0790 Assessment method.pdf 
                              2017/2018 spring
                              Julia Tammela, V - Estonian Maritime Academy
                              Estonian
                                VAY0790 Assessment method.pdf 
                                Course description in Estonian
                                Course description in English