Tilastot ja todennäköisyys (5 op)

Arviointiasteikko

H-5

Sisällön jaksotus

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

Topics include:
- 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

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

Teacher's materials in conjunction with the free online textbook: Introductory Statistics 2e by OpenStax.

For additional reading, the following book is recommended: Probability and Statistics (3rd edition), Murray R. Spiegel, John J. Schiller, R. Alu Srinivasan, SCHAUM’S outlines

Opetusmenetelmät

• Contact teaching: During lectures, we cover theory and example exercises. Applications of the theory in ICT are highlighted.

• Practice classes: During practice classes the focus is on the homework which the students practice independenly and/or in groups. Time is reserved for questions and revision. In addition, group exercises and formative tests are used as practice material.

• Independent work: Even though questions and interactivity are strongly supported during classes in TUAS there is a strong emphasis on a student's independent learning. The goal is to teach the student to assess their own learning and understanding, to search for information and revise independently.

Tenttien ajankohdat ja uusintamahdollisuudet

1st part-exam: week 43
2nd part-exam: week 50
The possibility to retake part-exams is organized in Dec/Jan (time to be announced later)

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. Lecture 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

The course may be completed with a special exam that proves the student's competence with the course topics. This must be agreed separately with the teacher. If the student is interested, they should contact the teacher.

Opiskelijan ajankäyttö ja kuormitus

Contact lessons and exams: 56 h (approx. 4 h / week)
Independent study, homework and preparation for part-exams: 70 h (approx. 5 h / week)

Arviointimenetelmät ja arvioinnin perusteet

The grade from the study unit is determined by the total number of points (max. 144).
• 96 p obtainable from the part exams (2 x 48 p)
• 32 p obtainable from homework sets (4 x 8 p)
• max 16 p from "activity". These points may be collected from three sources:
- Participating and returning Group exercises (max 8 p)
- Completing the Excel practice set (max 8 p)
- Completing the Tech task (max 8 p)

To pass the study unit, ALL the following requirements must be met:
• At least 20 points obtained from the exams (in total)
• At least 42 points obtained altogether

If the passing requirements are met, the grade boundaries are:
• 1: min. 42 p
• 2: min. 64 p
• 3: min. 86 p
• 4: min. 108 p
• 5: min. 130 p

Hylätty (0)

The student has shown to satisfactorily meet less than half of the course's basic learning goals.

• Exam points are less than 20 OR
• Points total are less than 42

Arviointikriteerit, tyydyttävä (1-2)

Student meets the passing criteria and the points total are less than 86.

The student has shown to satisfactorily meet the course's basic learning goals.

Arviointikriteerit, hyvä (3-4)

Student meets the passing criteria and the points total are between 86 and 129.

The student has shown to meet the course's basic learning goals well and advanced goals satisfactorily.

Arviointikriteerit, kiitettävä (5)

Student meets the passing criteria and the points total are at least 130.

The student has shown to meet the course's learning goals well.

Esitietovaatimukset

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

Lisätiedot

All practical information is provided in ITSLEARNING.

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. The teacher must be informed prior to beginning this project.