MJ5200 Climate journalism, theory and practice Course description

This course brings together theory and practice to explore the possibilities and challenges involved in contemporary reporting of climate and environmental issues. Climate change is a global problem, but it is experienced locally, as it is becoming a relevant dimension of ever more areas of life - and thus also across journalistic beats. Significant societal transformations need to take place over the next decade, and here journalism will have a key role to play. This course will help students pursue both the theoretical and practical development of climate journalism, including the understanding of journalism's own role in society, in a time of declared and perceived crisis.

Language of instruction is English.

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This course, together with Mathematics 1000, will give students an understanding of mathematical concepts, issues and solution methods with the focus on applications. The course will also give students an understanding of concepts in statistics and probability theory, problems and solution methods with the focus on applications in their own field and in the engineering field in general.

After completing the course, the student is expected to have achieved the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge The student is capable of:

• using linear algebra to determine eigenvalues and solving systems of differential equations and solving second order linear differential equations with constant coefficients
• discussing functions of multiple variables and apply partial derivatives to various problems
• explaining convergence and power series representations of functions
• explaining key concepts in set theory, probability theory, parameter estimation, hypothesis testing and choice of model
• explaining normal, binomial, Poisson and exponential probability distributions, as well as typical problems to which they can be applied

Skills

The student is capable of:

• calculating eigenvectors and diagonalising matrices
• applying diagonalisation of matrices to solve systems of differential equations
• determining the convergence of series using the ratio test, and finding the Taylor series of known functions
• describing and discussing functions of multiple variables using e.g. level curves and partial derivatives
• determining and classifying critical points of functions of two variables
• applying statistical principles and concepts from their own field
• basic calculus of probability with discrete and continuous probability distributions and parameter estimation
• calculating confidence intervals and testing hypotheses
• applying mathematical tools to matrices and functions of two variables

General competence

The student is capable of:

• identifying the connection between mathematics and their own field of engineering
• transferring a practical problem from their own field into mathematical form, so it can be solved analytically or numerically
• using mathematical methods and tools that are relevant to the field
• using statistical ways of thinking to solve problems in engineering and communicating them orally and in writing
• solving problems in engineering by use of probability calculations, statistical planning of trials, data collection and analysis

The course is taught through joint lectures and exercises. In the exercise sessions, the students work on assignments, both individually and in groups, under the supervision of a lecturer.

Individual written exam, 3 hours.

The exam result can be appealed.

In the event of resit and rescheduled exams, another exam form may also be used or a new assignment given with a new deadline. If oral exams are used, the result cannot be appealed.

Aids enclosed with the exam question paper, and a handheld calculator that cannot be used for wireless communication or to perform symbolic calculations. If the calculator’s internal memory can store data, the memory must be deleted before the exam. Random checks may be carried out.

Grade scale A-F.

The course builds on DAFE1000 Mathematics 1000.