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Statistical Methods and Optimisation (4 cr)

Code: BIM6023-3003

General information


Enrollment

01.10.2022 - 31.10.2022

Timing

09.01.2023 - 28.05.2023

Number of ECTS credits allocated

4 op

Mode of delivery

Contact teaching

Campus

Wärtsilä Campus Karjalankatu 3

Teaching languages

  • Finnish

Seats

10 - 70

Degree programmes

  • Degree Programme in Forestry

Teachers

  • Jani Kangas

Teacher in charge

Jani Kangas

Groups

  • MMNS21
    Forestry Engineer, Full-time Studies, Fall, 2021

Objective

-

Content

-

Materials

Tilastollisten menetelmien perusteet: Lauri Nummenmaa, Martti Holopainen, Pekka Pulkkinen
ISBN 978-952-63-2979-6

You don't have to have it, but it's good supporting material

Teaching methods

Lectures and exercises

Student workload

Lectures 44 h
Practical work: 30 h
Independent study: 25 h
Exam: 3 h
Feedback: 5 h

Evaluation scale

H-5

Assessment methods and criteria

The assessment is based on an exam for statistical mathematics and exercises for optimisation. The grade of the course is determined by the exam in statistical mathematics.

Assessment criteria, fail (0)

The student does not know how to use key/unique concepts of statistical mathematics and optimisation.

Assessment criteria, satisfactory (1-2)

Students will be able to use key/unique concepts of statistical mathematics and optimisation and demonstrate a basic knowledge of the domain.
The student will be able to act appropriately in solving simple problems in statistics and optimisation, albeit in a fumbling way. The student will be able to follow instructions and solve basic problems in statistical mathematics and optimisation.

Assessment criteria, good (3-4)

Students will be able to use the concepts of statistical mathematics and optimisation consistently and demonstrate a basic knowledge of the domain.
Students will be able to select appropriate ways of modelling simple problems in statistics and optimisation. Students will be able to solve basic problems in statistics and optimisation and to assess their own competence. The student can apply his/her knowledge in basic tasks.

Assessment criteria, excellent (5)

Students will be able to use the terms and concepts of statistical mathematics and optimisation in a competent way and to combine them in a coherent way.
Students will be able to model and solve simple problems in statistics and optimisation and to evaluate the correctness of the solutions. Students will be able to apply their knowledge of statistical mathematics and optimisation in a variety of tasks and situations.