Data Analysis
BASIC DATA
course listing
A - main register
course code
RAM0580
course title in Estonian
Andmeanalüüs
course title in English
Data Analysis
course volume CP
4.00
ECTS credits
6.00
to be declared
yes
assessment form
Examination
teaching semester
autumn - spring
language of instruction
Estonian
English
Prerequisite(s)
Prerequisite 1
Mathematical Analysis (NTS1730)
The course is a prerequisite
Data Science and Machine Learning (EVR0350)
Study programmes that contain the course
code of the study programme version
course compulsory
EDTR17/25
yes
MAJB24/25
yes
Structural units teaching the course
ET - Tartu College
EV - Virumaa College
Course description link
Timetable link
View the timetable
Version:
VERSION SPECIFIC DATA
course aims in Estonian
Anda teadmisi juhuslike nähtuste seaduspärasuste kohta ning oskusi nende seaduspärasuste kindlakstegemiseks ja kirjeldamiseks. Õpetada lahendama tõenäosusteooriaga seotud põhilisi ülesandeid. Anda teadmisi kirjeldavast statistikast, statistiliste hüpoteeside kontrollimisest ja andmeanalüüsi enamkasutatavatest meetoditest. Arendada oskusi sobivate andmeanalüüsi meetodite valimiseks ja nende rakendamiseks, andmeanalüüsi tulemuste korrektseks vormistamiseks ja tõlgendamiseks. Anda vastava tarkvara kasutamise oskus.
course aims in English
To give the knowledge about the laws of random phenomena and ability to identify them. To teach solving basic tasks connected with the probability theory. To give knowledge of descriptive statistics, statistical hypotheses control and most commonly used methods of data analysis. To develop skills of selecting and applying appropriate data analysis methods, presenting and interpreting data analysis results. To give skills of using relevant software.
learning outcomes in the course in Est.
Üliõpilane tunneb tõenäosusteooria põhimõisteid ja omadusi, tunneb enamlevinuid statistilisi jaotusi ja nende omadusi. Suudab oma teoreetilisi teadmisi rakendada mainitud teooriaga seotud ülesannete lahendamisel. Tunneb kirjeldava statistika ja andmeanalüüsi põhimeetodeid. Oskab püstitada statistilisi hüpoteese, valida andmetele ja ülesande püstitusele vastavat andmeanalüüsi meetodit ja rakendatud meetodi tulemusi tõlgendada. Oskab andmeanalüüsi tulemusi nõuetekohaselt vormistada. Oskab kasutada vähemalt ühte andmetöötluse tarkvara.
learning outcomes in the course in Eng.
Student knows the main concepts and properties of the theory of probability, knows the most common statistical distributions and their properties. Is able to apply one’s theoretical knowledge in solving tasks connected with the theory mentioned above. Knows the main methods of descriptive statistics and the basic methods of data analysis; can set statistical hypotheses; can select a data analysis method corresponding with the type of data and task aims as well as interpret the results of the implemented method; is able to format the results of data analysis according to the set requirements; can use at least one data processing software.
brief description of the course in Estonian
Tõenäosusteooria põhimõisted ja -seosed. Tinglik tõenäosus. Täistõenäosus ja Bayesi valem. Bernoulli valem. Juhusliku suuruse jaotusfunktsioon ja jaotustihedus. Juhusliku suuruse arvkarakteristikud. Enamlevinud jaotused. Piirteoreemid. Statistiliste andmete kirjeldamine ja näitlikustamine. Väljavõtteliste jaotuste arvkarakteristikute hindamine. Hüpoteeside püstitamine ja kontrollimine. Statistiline sõltuvus. Korrelatsioon- ja regressioonanalüüs. Dispersioonanalüüs. Järelduste sõnastamine, tulemuste vormistamine ja visualiseerimine, statistika tarkvara kasutamine.
brief description of the course in English
Main concepts and relations of probability theory. Conditional probability. Total probability and Bayes theorem. Bernoulli's formula. Distribution function and distribution density of a random variable. Numerical characteristics of random variables. The most relevant distributions. Limit theorems. Describing and visualization of statistical data. Sampling distributions. The estimation of parameters. Setting and testing hypotheses. Statistical dependence. Correlation and regression analysis. Analysis of variance. Formulating conclusions, formatting and visualization of results, using statistical software.
type of assessment in Estonian
vt fail
type of assessment in English
see attachment
independent study in Estonian
Iseseisev töö on mõeldud aine teoreetilise osa iseseisvaks läbitöötamiseks, harjutusülesannete lahendamiseks ja iseseisva töö (projekti) ülesannete täitmiseks. Semestri jooksul tuleb sooritada kontrolltööd ja kodutööd. Kodu- ja kontrolltööde arvu ja eksami läbiviimise vormi määrab õppejõud semestri alguses. Iseseiseva töö (projekti) sisuks on kursuses esitatud meetodite kasutamine üliõpilaste poolt kogutud reaalse andmestiku analüüsimisel, saadud tulemustest järelduste tegemisel ning nende tõlgendamisel ja nõuetekohaselt vormistamisel. Projekt sooritatakse rühmatööna. Projekti nõuded määrab õppejõud semestri alguses.
independent study in English
Independent work is meant for independent working through the theoretical part of the subject, tests and home tasks solving and compiling an independent task (project). The students have to submit tests and home tasks during the semester. The number of hometasks and quizes as well as examination prerequisites and form is defined by the course instructor at the beginning of the semester. The project represents analysis of data collected by the student using the methods studied in the course, interpretation and formatting of results according to the set requirements. Project is carried out as teamwork. The project requirements are defined by the course instructor at the beginning of the semester.
study literature
Jõgi, A. Tõenäosusteooria I, II. Tallinn, 2000;
Tammeraid, I. Tõenäosusteooria ja matemaatiline statistika. Tallinn, 2004;
Prem S. Mann. Introductory Statistics. Wiley 2006;
Parring A.-M., Vähi, M., Käärik, E. Statistilise andmetöötluse algõpetus. Tartu, 1997.

study forms and load
daytime study: weekly hours
4.0
session-based study work load (in a semester):
lectures
2.0
lectures
8.0
practices
0.0
practices
0.0
exercises
2.0
exercises
12.0
lecturer in charge
-
LECTURER SYLLABUS INFO
semester of studies
teaching lecturer / unit
language of instruction
Extended syllabus
2025/2026 autumn
Meelis Zimmermann, ET - Tartu College
Estonian
    RAM0580_AA_TT_hindamine_Eng.pdf 
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    2024/2025 spring
    Olga Dunajeva, EV - Virumaa College
    Estonian
      RAM0580_AA_TT_hindamine_Eng.pdf 
      2024/2025 autumn
      Meelis Zimmermann, ET - Tartu College
      Estonian
        RAM0580_AA_TT_hindamine_Eng.pdf 
        2023/2024 spring
        Olga Dunajeva, EV - Virumaa College
        Estonian
          2023/2024 autumn
          Meelis Zimmermann, ET - Tartu College
          Estonian
            2022/2023 spring
            Olga Dunajeva, EV - Virumaa College
            Estonian
              2022/2023 autumn
              Meelis Zimmermann, ET - Tartu College
              Estonian
                2021/2022 spring
                Olga Dunajeva, EV - Virumaa College
                Estonian
                  RAM0580_AA_TT_hindamine_Eng.pdf 
                  2021/2022 autumn
                  Meelis Zimmermann, ET - Tartu College
                  Estonian
                    RAM0580_AA_TT_hindamine_Eng.pdf 
                    2020/2021 spring
                    Olga Dunajeva, EV - Virumaa College
                    Estonian
                      RAM0580_AA_TT_hindamine_Eng.pdf 
                      2020/2021 autumn
                      Meelis Zimmermann, ET - Tartu College
                      Estonian
                        RAM0580_AA_TT_hindamine_Eng.pdf 
                        2019/2020 spring
                        Olga Dunajeva, EV - Virumaa College
                        Estonian
                          RAM0580_AA_TT_hindamine_Eng.pdf 
                          2018/2019 spring
                          Olga Dunajeva, EV - Virumaa College
                          Estonian
                            RAM0580_AA_TT_hindamine_Eng.pdf 
                            Course description in Estonian
                            Course description in English