Code | DMS270 |

Name | Mathematics for Economists |

Status | Compulsory/Courses of Limited Choice |

Level and type | Undergraduate Studies, Professional |

Field of study | Mathematics and Statistics |

Faculty | |

Academic staff | Jevgeņijs Carkovs, Māris Buiķis, Andrejs Matvejevs, Nataļja Budkina, Oksana Pavļenko, Aija Pola, Marija Dobkeviča, Daina Pūre, Evija Liepa |

Credit points | 4.0 (6.0 ECTS) |

Parts | 1 |

Annotation |
Partial derivatives and elasticities for several argument functions. Substitution rate and elasticity. Optimization problems and applications in economics. Elements of probability theory: algebra of events, discrete and continuous random variables. Normal,exponential and Poisson's distributions. Elements of mathematical statistics.. |

Goals and objectives of the course in terms of competences and skills |
Deliver basic mathematical concepts that are necessary to understand basic tools that are used to analyze economic problems. Develop students’ logical thinking and skills to analyse basic aspects of specialty subjects with an objective to analyse more complicated problems. |

Learning outcomes and assessment |
After successful completion of the course, students can calculate partial derivatives of a function of several variables, compute differentials, find extrema of a function of several variables, expand a function in Taylor series. - One test, one homework assignment and several problems in the final exam are used to assess students’ knowlegde on these topics. Can use differential calculus of several variables to analyse optimization problems in economics, analyse price elasticity of demand. - Corresponding problems are included in the final exam. After successful completion of the course, students will be able to solve problems in probability theory, perform descriptive statistics analysis and use differential calculus of several variables. - Evaluation of students’ work is based on the results of homework assignments, tests and the final exam. Can use the rules of probability, obtain discrete probability distribution, analyze binomial distribution and Poisson distribution. - Students’ knowledge and abilities are assessed using homework assignments, tests and the final exam. Can solve problems related to normal distribution, use the table of the Laplace's function, perform operations using probability density function and cumulative probability distribution function. - One test, one homework assignment and several problems in the final exam are used to assess students’ knowledge on these topics. Can perform decsriptive statistics analysis of data, develop confidence intervals and perform hypothesis testing. - Students’ work is tested using homework assignment and a problem in the final exam. |

Course prerequisites |

[Extended course information PDF]