Learning outcome

After successfully completing the course, the candidate will have achieved the following learning outcomes defined in terms of knowledge, skills and general competence.

Knowledge

The candidate has basic knowledge of:

• Descriptive statistics, combinatorics, probability and statistical methods, and is able to design relevant problems and interpret results and graphics in an adequate manner
• Electrotechnology and electromagnetism, and is able to design relevant problems and interpret results in an adequate manner

Skills

The candidate can:

• Create simple graphics and perform simple statistical and physics-related calculations without using a computer within the areas the candidate should have knowledge of
• Relate electrotechnology and electromagnetic theory to problems by performing relevant calculations and arguments
• Use the computer program Maple to generate illustrations, and carry out complex statistical calculations
• Conduct polls and surveys that form the basis of good information management in terms of calculations and reasoning

General competence

The candidate has:

• Developed a precise use of language that facilitates communication with others about problems related to statistics and basic electrotechnology
• Developed an awareness that there are important ethical issues related to the collection, analysis, presentation and interpretation of data
• Developed awareness of the importance of mathematical formalism for solving problems using mathematical models

Course Description

Statistics – 5 credits
Descriptive statistics. Probability. Conditional probability. Overview of discrete and continuous stochastic variables, expectation and variance. Special focus on binomial, hypergeometric, Poisson, normal and exponential distribution. Sum of stochastic variables. Central limit theorem. Estimation and confidence intervals. Hypothesis testing and regression analysis. Risk and reliability.

Physics – 5 credits
Electric charge, field and flux. Gauss’s law. Electrical potential. Capacitance and capacitors. Electricity. Resistance and Ohm’s law. Electric power. Electromagnetic induction. Faraday’s law. Electric motors

Teaching and Learning Methods

Lectures, exercises, compulsory exercises.

Motivation
The lectures will provide an overview of the course’s academic content (knowledge) and encourage students to work independently (skills), for example by reviewing examples and exploring possibilities with the use of computers.
The exercises require that students themselves are active (skills). Under supervision, working with exercises can lead to deeper understanding (knowledge) of the interaction between instrumental activities and theory.
Group work is also necessary in order to develop students’ communicative abilities in statistics and physics (general competence). In addition, group work can include challenging assignments that require creativity and innovation (knowledge).

Assessment Methods

Final individual written examination in Physics, weighted 50%, which is assessed with a letter grade. Compulsory exercises. Examination aids: calculator and “Formler og tabeller” by John Haugan (without handwritten notes).
Mandatory statistics lab sessions with accompanying reports must be approved to grade the Statistics part.
Final individual written examination in statistics, weighted 50%. All written and printed examination aids are allowed, as well as a computer; assessed with a letter grade.
Both final examinations must be passed with a grade E or better in order to achieve a passing grade in the course.

Motivation
The final examinations will assess the extent to which the individual student has achieved the learning outcomes in terms of knowledge and skills in statistics and possibly physics. Group work will also assess the extent the student is able to communicate with others in a group, as well as through written reports on the subject of statistics.

Minor adjustments may occur during the academic year, subject to the decision of the Dean