Applied statistics
BASIC DATA
course listing
A - main register
course code
YKA0013
course title in Estonian
Rakendusstatistika
course title in English
Applied statistics
course volume CP
-
ECTS credits
3.00
to be declared
yes
assessment form
Examination
teaching semester
autumn - spring
language of instruction
Estonian
English
Study programmes that contain the course
Structural units teaching the course
LK - Department of Chemistry and Biotechnology
Timetable link
Version:
VERSION SPECIFIC DATA
course aims in Estonian
Anda õppurile ettekujutus teaduses enamkasutatavatest andmeanalüüsi meetoditest ja kujundada nende kasutamiseks praktilisi oskusi.
course aims in English
The aim of the course is to give a student an idea of data analysis methods used in science and engineering and give practical skills for their using.
learning outcomes in the course in Est.
Kursuse läbimisel üliõpilane
- tunneb tõenäosusteooria põhimõisteid
- tunneb statistika põhimõisteid (punkthinnangud, hüpoteeside testimine, katsete planeerimine)
- suudab formuleerida statistilisi hüpoteese ja neid kontrollida oma erialal ette tulevate probleemide kontrollimiseks
- valdab tuntumaid tarkvarapakette statistilise analüüsi läbiviimiseks
- oskab läbi viia lineaarset/mittelineaarset regressioonanalüüsi ja lähendada teoreetilisi mudeleid
- oskab planeerida oma eksperimente
- tunneb tõenäosusteooria põhimõisteid
- tunneb statistika põhimõisteid (punkthinnangud, hüpoteeside testimine, katsete planeerimine)
- suudab formuleerida statistilisi hüpoteese ja neid kontrollida oma erialal ette tulevate probleemide kontrollimiseks
- valdab tuntumaid tarkvarapakette statistilise analüüsi läbiviimiseks
- oskab läbi viia lineaarset/mittelineaarset regressioonanalüüsi ja lähendada teoreetilisi mudeleid
- oskab planeerida oma eksperimente
learning outcomes in the course in Eng.
After passing the course a student
- knows main concepts of probability theory
- knows main concepts of statistics (point estimates, testing hypothesis, design of experiments)
- can formulate statistical hypothesis in its field and test them competently
- can operate with popular statistical packages
- can design experiments in its specific field of competence
- knows main concepts of probability theory
- knows main concepts of statistics (point estimates, testing hypothesis, design of experiments)
- can formulate statistical hypothesis in its field and test them competently
- can operate with popular statistical packages
- can design experiments in its specific field of competence
brief description of the course in Estonian
Tõenäosuse definitsioon ja tõenäosuste liitmine ja korrutamine. Juhusliku suuruse jaotusfunktsioonid (normaal, F, binomiaalne ja Poissoni jaotusfunktsioonid). Keskväärtus ja variatsioon, vigade liigid ja vigade levimise seadus.
Punkthinnangud, usaldusvahemikud ja hüpoteeside testimine.
Univariantne ja multivariantne lineaarne regression.
Katsete planeerimine ja variatsioonanalüüs.
Punkthinnangud, usaldusvahemikud ja hüpoteeside testimine.
Univariantne ja multivariantne lineaarne regression.
Katsete planeerimine ja variatsioonanalüüs.
brief description of the course in English
Probability definition and operations with probablility. Probability density distributions (with emphasis on normal, binomial, F and Poisson distributions), expectation, variance, different kinds of errors, and propagation of errors.
Point estimates, confidence intervals, and hypothesis testing.
Simple and multiple linear regression,
Design of experiments, 2² and 2³ factorial designs, and analysis of variance.
Point estimates, confidence intervals, and hypothesis testing.
Simple and multiple linear regression,
Design of experiments, 2² and 2³ factorial designs, and analysis of variance.
type of assessment in Estonian
Kontrolltöö (20%), kolm kodutööd (60%) ja eksam (20%).
type of assessment in English
Test (20%), three take home projects (60%) and exam (20%).
independent study in Estonian
Kodutööd ja teadusartiklite lugemine (õppejõu soovitusel)
independent study in English
Take home projects and reading papers.
study literature
James N Miller, Jane C Miller, "Statistics and Chemometrics for Analytical Chemistry", Sixth edition, © Pearson Education Limited, 2010.
study forms and load
daytime study: weekly hours
2.0
session-based study work load (in a semester):
lectures
1.0
lectures
-
practices
0.0
practices
-
exercises
1.0
exercises
-
lecturer in charge
-
LECTURER SYLLABUS INFO
semester of studies
teaching lecturer / unit
language of instruction
Extended syllabus
2025/2026 autumn