Opinto-opas

Tavoitteet

Opintojakson suoritettuaan opiskelija osaa:
- laskea erilaisia keski- ja hajontalukuja annetulle tilastolliselle aineistolle
- määrittää regressiosuoran ja korrelaation, sekä ymmärtää niiden merkityksen
- tunnistaa ja piirtää erilaisia tilastollisia diagrammeja
- jatkuvan ja diskreetin todennäköisyysjakaumien peruskäsitteet
- normittaa normaalijakautuneen muuttujan ja laskea siihen liittyviä todennäköisyyksiä
- laskea luottamusvälejä ja ymmärtää virheen merkityksen tilastollisessa matematiikassa
- määrittää p-arvoja keskiarvon z- ja t-testillä
- luoda frekvenssitaulukon ja soveltaa siihen khiin neliö -testiä
- hyödyntää tietotekniikkaa tilastollisen datan käsittelyssä ja analysoinnissa

Sisältö

- keskiluvut, hajontaluvut
- diagrammit ja niiden erot
- regressio, korrelaatio
- todennäköisyyden perusmääritelmät ja -kaavat
- diskreetti todennäköisyysjakauma, binomijakauma, Poisson-jakauma
- jatkuva todennäköisyysjakauma, normaalijakauma, normittaminen
- tilastollinen testaaminen, otantatutkimus, luottamusväli
- keskiarvon z-testi ja t-testi
- frekvenssitaulukko ja khiin neliö -testi

Oppimateriaalit

All course material and links to outside materials are on ITSlearning.

Opetusmenetelmät

Lectures, exercises, homework, guided practice, project work, independent study

Tenttien ajankohdat ja uusintamahdollisuudet

Part-exam 1 will take place on week 44.
Part-exam 2 will take place on week 50.

There will be an opportunity to retake both part-exams in January 2025.

Pedagogiset toimintatavat ja kestävä kehitys

During the course we will learn statistical and probability skills and knowledge fundamental for an ICT-engineer's profession. Various forms of technology are widely used in all topics and students are encouraged to learn more ways to use technology in solving problems within the course's topics. A lot of learning happens in class with the guidance of the teacher but independent study and homework is important as well.

Sustainable development aspects are considered during the course. Lesson material and homework feature examples about creating an ecologically sustainable and resilient society, and the impact of statistics in promoting sustainable development is discussed.

Toteutuksen valinnaiset suoritustavat

If a student wants to pass the course by taking only an exam, this needs to be agreed upon with the teacher.

Opiskelijan ajankäyttö ja kuormitus

Contact hours: 28 h (lectures) + 24 h (homework classes) = 52 h
Exams: 4 h
Independent study (homework, exam preparation, extra task etc.): 74 h

Sisällön jaksotus

The course will begin on week 36 and end on week 50.

Topics:
- mean and standard deviation figures
- diagrams and their differences
- regression, correlation
- basic definitions and formulas of probability
- discrete probability distribution, binomial distribution, Poisson distribution
- continuous probability distribution, normal distribution, normalization
- statistical testing, sampling, confidence interval
- z-test and t-test of average
- contingency tables and chi-square test

Viestintäkanava ja lisätietoja

It is possible to do an optional statistical project during the course which will give you an extra 2 credits, i.e. a total of 7 credits. This project will be about a topic of your own choosing (with the help of the teacher) and you are expected to use a wide range of statistical and/or probabilistic methods in it. You are expected to gather, process, present and analyse data and produce a report about it, to be submitted by the end of the course by an agreed upon deadline. It is expected that you devote approximately 30-50 hours of work into this. The report won't affect your course grade but, if it contains the required elements and is of an appropriate depth, you will get the 2 extra credits.

More detailed instructions and requirements as well as a template file can be found on ITS. Email the teacher before you start doing the project so that no two students come up with too similar topics.

Arviointiasteikko

H-5

Arviointimenetelmät ja arvioinnin perusteet

The assessment consists of:
- Two part-exams (2x50 p = 100 p). Part-exam 1 is on week 44, part-exam 2 on week 50.
- Homework (84 p)
- Attendance (6 p)
- Extra task (10 p)
Total: 200 p

To pass, the total points obtained must be at least 70, and at least 30 of them must come from the part-exams.

Attendance is taken at the start of each lecture, excluding the first one. At the end of the course, based on the number of attendances, you’ll receive the following number of points:
7: 1 p
8: 2 p
9: 3 p
10: 4 p
11: 5 p
12-13: 6 p

There are 12 topics, each has some homework questions on ITS and a set of homework questions to be submitted. Each topic's homework gives 7 p in total.

The extra task is work up to 10 p and can be completed by the deadline set by the teacher. This task is about learning how to use some technology not covered during classes.

Grade boundaries:
0-69: FAIL
70-93: 1
94-117: 2
118-141: 3
142-165: 4
166-200: 5

Hylätty (0)

Fewer than 70 points
and
fewer than 30 points from the part-exams

Arviointikriteerit, tyydyttävä (1-2)

70-93 points: 1
94-117 points: 2

And at least 30 points obtained from the part-exams

Arviointikriteerit, hyvä (3-4)

118-141 points: 3
142-165 points: 4

And at least 30 points obtained from the part-exams

Arviointikriteerit, kiitettävä (5)

166-200 points: 5

And at least 30 points obtained from the part-exams

Esitietovaatimukset

Insinöörimatematiikan perusteet, Calculus ja Soveltava matematiikka -opintojaksojen sisällöt
TAI
vastaavat tiedot ja taidot