Probability and Statistics (5 cr)

Materials

Johnson, R. (2008) Miller and Freund’s Probability and Statistics for Engineers

Evaluation scale

0-5

Completion alternatives

- Exams 80–90 % - Exercises or assignments 10–20 %

Further information

Alternative Finnish implementation: Tilastomatematiikka, TLXM3580

Student workload

- Lectures 40–60 h - Independent study 60–90 h - Exams 2 h Total 100–150 h

Assessment criteria, satisfactory (1)

Excellent (5): Student has attained an excellent level of course objectives and can apply them into practice in innovative manner.
Very good (4): Student has attained very good level of course objectives and can apply them into practice.
Good (3): Student has gained understanding of course objectives and can utilize them in practice.
Satisfactory (2): Student has gained knowledge of course objectives and can utilize them partly in practice.
Sufficient (1): Student has gained knowledge of course objectives but face challenges to utilize them in practice.

Teaching language

en

Location and time

Lessons are on weeks 37 - 50
1,5 h in computer lab
typically 2 times per week

Number of ECTS credits allocated

5

Qualifications

Algebra and Geometry, and Calculus

Content

Elements of probability and statistics, probability distributions, confidence level estimation and hypotheses testing, regression analysis, reliability calculations. The use of mathematical computer programs.

Objective

The students identify statistical and stochastic ideas, concepts and methods and can apply them to solve work-oriented problems using a computer. The students are able to draw conclusions, estimate risk and calculate reliability based on statistical data.
EUR-ACE Knowledge and Understanding: Students must know and understand the statistical principles, concepts and methods underlying logistics.
EUR-ACE Engineering Analysis: Students must have the ability to identify, formulate and solve engineering problems using statistical methods.
EUR-ACE Investigations: Students must have the ability to apply data bases and to design and conduct appropriate experiments, interpret the data and draw conclusions.
TELNA: Students are able to use mathematics and statistics in a technical environment.