Quantitative methods for agriculture and environment science (169512)
Course coordinator
Course description
Calculus: Exploring of mathematical approaches and solutions that cut across agriculture and environmental disciplines and introducing of analytical techniques that are thought infrequently in other courses. The goal is to provide students with the tools and confidence they need to apply quantitative methods in their own research (differential and integral calculus, multivariable calculus, with examples and applications from the environmental sciences).
Type of course
- Graduate studies / Environment, agriculture and resource management (Compulsory course, 1 semester, 1 year)
ECTS: 3.00
Teaching hours: 30
Lectures: 20
Auditory exercises: 10
Lecturer
Associate teacher for exercises
Grading
Sufficient (2): 60-70 %
Good (3): 71-80 %
Very good (4): 81 -90%
Excellent (5): 91-100%
General competencies
This course introduces the use of quantitative methods in environmental analysis. Students will learn how to apply basic principles of natural science to a variety of globally important problems.
Types of instruction
- Lectures
- Auditory Exercises
- Practicum
Learning outcomes
Learning outcome | Evaluation methods |
---|---|
have working knowledge of basic concepts, methods and techniques from calculus; | exam, practical work, project |
be able to apply mathematical knowledge, insights and methods to solve basic problems in life sciences (agriculture and environment) using a systematic approach; | exam, practical work, project |
be able to critically reflect upon the results; | exam, practical work, project |
be able to interpret the results in terms of the problem that was modelled mathematically; | exam, practical work, project |
be able to use mathematical software in elaborating mathematical models. | exam, practical work, project |
Working methods
Teachers' obligations
1. Course planning
2. Selection and creation of teaching materials
3. Evaluation of course, teaching materials and curriculum
4. Construct tests
5. Grade students on the basis of their achievement
Students' obligations
1. Attend lectures regularly
2. Do homeworks and participate actively during lectures
3. Write tests and win at least 25% of points on each test to get the signature
4. Do individual projects
Methods of grading
Evaluation elements | Maximum points or Share in evaluation | Grade rating scale | Grade | Direct teaching hours | Total number of average student workload | ECTS |
---|---|---|---|---|---|---|
1st exam | 40 % | 14 | 20 | 1 | ||
2nd exam | 30 % | 8 | 20 | 1 | ||
3rd exam | 30 % | 8 | 20 | 1 | ||
activity | up to 10 % | |||||
Total | 100 % | 30 | 60 | 3 |
Evaluation elements | Description | Deadline | Recoupment |
---|---|---|---|
3rd Exam | functions of several variables | 16th week |
Weekly class schedule
- Introduction L - Survey of elementary functions. Real functions of one real variable
- Differential of a function L - Limit, derivative, interpretations of derivative, differential of a function, tabular differentiation
- Differentiation techniques E - Differentiation techniques, higher order derivatives
- Minimum and maximum problems I L+E - Applications to minimum and maximum problems
- Minimum and maximum problems II E - Exercises on minimum and maximum problems
- Integration I L - Definite and indefinite integrals, Newton-Leibnitz formula
- Integration II E - Methods of finding indefinite integrals
- Differential equations I L - Basic concepts and methods of solving
- Differential equations II L+E - Methods of solving
- Differential equations III E - Solving differential equations
- Matrix algebra I L - Survey of matrix algebra, determinants, eigenvalues and eigenvectors
- Matrix algebra II E - Exercises on matrix algebra
- Functions of several variables I L - Partial derivatives and differentials of functions of several variables
- Functions of several variables II L+E - Maximum and minimum of functions of several variables
- Functions of several variables III E - Exercises on maximum and minimum of functions of several variables
Recommended literature
- L. D. Hoffman, G. L. Bradley: Calculus for Business, Economics, and the Social and Life Sciences
- K. Sydsaeter, P. J. Hammond: Mathematics for Economic Analysis, Prentice Hall, 2002
- K. Sydsaeter, P. J. Hammond, A. Seierstad, A. Strom: Further Mathematics for Economic Analysis, Prentice Hall, 2008
- M. W. Klein: Mathematical methods for economics, Pearson Education, 2002.
Similar course at related universities
- Mathematik, BOKU, Wien
- Mathematik und Statistik, Agricultural Sciences, University of Hohenheim