Mathematics for the social sciences - programme subject in programmes for Specialization in General Studies (MAT4-01)
Utgått
Denne læreplanen har utgått.
Mathematics S1
Algebra
- work with powers, formulae, brackets and rational and quadratic expressions with numerals and letters
- convert a practical problem into an equation, an inequality or a system of equations, solve it and assess the validity of the solution
- solve equations, inequality and systems of equations of the first and second degree, in longhand and by digital means
- calculate with logarithms and use them to simplify expressions and solve exponential equations and logarithmic equations
- use the concepts of implementation and equivalence in mathematical reasoning
Functions
- draw graphs of polynomial functions, exponential functions, power functions and rational functions with linear numerators and denominators with and without digital means
- create and interpret functions as models and describe practical problems in economics and social science, analyze empirical functions and use regression to find a polynomial approximation of a function, power function or exponential function
- determine zero points and intersection points between graphs, with and without digital means
- find the average growth rate for a function arithmetically, and find approximate values for momentary growth in practical applications
- give an account of the definition of the derivative, work out the derivative for polynomial functions and use this to discuss polynomial functions
Probability
- work with binomial coefficients and construct Pascal’s Triangle
- give an account of non-random selection with and without replacement and random selection without replacement, and carry out simple probability calculations linked to such selections
- create binomial and hypergeometric probability models from practical situations, and work out probabilities for such models
Linear optimization
- model practical optimization problems in economics using linear equations and incongruence
- give an account of the geometrical interpretation of the linear optimization problem in two variables
- solve linear optimization problems graphically, using longhand and digital means
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