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Objective(s) of a study programme: The objective of Applied Mathematics bachelor study program is to prepare specialists, who will have: a) relevant knowledge in mathematics and its application, practical sills for mathematical techniques and communication; b) abilities to think logically, to develop software tools for real world objects (events, situations) mathematical model analysis, to analyse and critically evaluate the data and results, to provide information, to work in team, to organize the work, to develop constantly professionalism, and uphold the values of higher education. Learning outcomes: Knowledge and its application: Have knowledge and understanding of the basic concepts, definitions and proofs from major areas of mathematics (algebra, mathematical analysis, geometry, differential equations, probability theory and statistics and ability to apply them to the solution of theoretical and real problems. Have knowledge and understanding of a range of mathematical methods used to develop and analyse mathematical models coming from various interdisciplinary application areas. Have knowledge of the main numerical methods and understanding of some pitfalls of mathematical approximation and mathematical computing. Demonstrate a reasonable understanding of the modelling principles and ability to apply mathematics to real situations, using deterministic or probabilistic models. Have knowledge and understanding of the theory of algorithms and programming, their applicability conditions in developing mathema ...
Provider NameKaunas University of Technology
Objective(s) of a study programme: To prepare the creative mathematics graduates of broad erudition with actual knowledge in mathematics and its applications and be able to explore, simulate and responsibly apply in the new situations, to evaluate decisions, and to pick out the best and so develop their personal career in the chosen area, also will be able to be competent partners in joint projects with the other academic specialists. Learning outcomes: Knowledge and its application modeling principles and their application possibilities in technological, physical, economical, medical and sociological sciences; Financial and actuarial mathematics theory and its application for modeling financial markets; risk and decision-making theory and its application; principles of optimal process theory; statistical analysis methods of multidimensional data; analysis of formal specifications of software systems. Abilities to carry out research see modeling possibilities and be able to develop technology, finance, economics, social science and other areas of problem-solving mathematical models, base their relevance; be able to select and apply appropriate research methods from the available data or conditions; to detect and synthesize information throughout the solution process; to analyze given propositions critically, to compare and to assess them, to to choose optimal decisions, to draw reasonable conclusions, to make prognosis. Special abilities to create mathematical models of different systems and software ...
Provider NameKaunas University of Technology
Objective(s) of a study programme: The aim of the Applied Mathematics programme is to prepare broad-minded specialists with strong background and adequate skills for applying and developing of mathematical models for industry, business, finance and other areas. Learning outcomes: Graduates of the programme will be able to 1. Apply knowledge of mathematics and develop mathematical models for industry, business, finance and other areas. 2. Perform scientific investigations in mathematical modelling, data analysis, control fields, and develop software. 3. Apply newest knowledge of mathematics in solving problems of various dynamic processes. 4. Independently deepens and expands knowledge of application of mathematics. Activities of teaching and learning: Lectures, practical work, seminars, laboratory work, individual work, reading literature, solving problem tasks, preparation for lab work, midterm and final exams. Methods of assessment of learning achievements: Knowledge and skills are evaluated using criteria-based study achievement assessment system of a 10 mark scale. Study results are evaluated during the semester through the intermediate exams (mid-term exams, practical, laboratory work) and the final exam. Final and mid-term exams are performed in the written form. The final evaluation consists of weighting marks of each assessment. Specialisations: - Optional courses: It is possible: deepen subject areas knowledge, choosing a specialized field of study subjects; choose a variety of related studies offered ...
Provider NameVytautas Magnus University
The future Masters in Statistics study the following extension courses: Statistical Software Systems, Insurance Mathematical Models, Statistical Analysis by Sampling Methods, Statistical Models in Economics, Mathematical Models of Financial Markets, Analysis and Forecasting of Economical Indicators. The three following general courses are studied: Operation Research, Fundamentals of Theory of Stochastic Approximation and Data Analysis Methods. ...
Provider NameVilnius Gediminas Technical University
Objective(s) of a study programme: Objective is to develop internationally competitive specialists who are able to find a consistent pattern of large data arrays, and provide practical guidance based fulfillment of tasks. Partial goals and skills: • Ability to plan experiments, statistical data collection and to prepare them for further analysis • Ability to apply statistical models and real data analysis (classical antiquities smells can be replaced - "modern") • Can perform real data statistical analysis software packages help • Critically review and summary of the results is able to properly present the findings and recommendations applicable to the scope of the analysis and understanding of other professionals Learning outcomes: • Has the foundations of mathematics and statistics and is able to put the knowledge into statistical work in practice • Is able to use statistics / mathematics software for statistical work in practice • Has the knowledge of statistical applications in different fields (especially ecology, environment) and is able to adapt statistical work in practice. • Is able to formulate research work aims and objectives, plan of statistical surveys; prepare reports of statistical data analysis, interpret the results of statistical analysis, to formulate conclusions also apply known techniques of statistical information; • Ability to carry out statistical projects while working independently and in a group. • Adequately perceive the role of statistics, communicate constructively with colleagues ...
Provider NameKlaipeda University
Taikomosios statistikos ir ekonometrijos studijų programos tikslas - parengti statistikos bakalaurus, turinčius teorinių ir praktinių žinių apie statistinės duomenų analizės metodus bei modelius ir sugebančius šias žinias taikyti realiems ekonomikos, ūkio, draudos, finansų rinkų, biomedicinos, biologijos, sociologijos, technikos uždaviniams spręsti. Būsimieji statistikos bakalaurai studijuoja šiuos kvalifikacijos dalykus: Mikroekonomika, Makroekonomika, Ekonometrija 1, 2, Duomenų analizė, Technometrija, Statistinė kokybės kontrolė, Ūkio statistika, Imčių metodai, Statistinė programinė įranga, Masinio aptarnavimo teorija, Statistinė investicijų analizė, Duomenų bazių valdymas. Visi būsimieji statistikos bakalaurai turi atlikti pažintinę (3 kreditai) ir gamybinę praktiką, kuri yra 12 kreditų apimties. ...
Provider NameVilnius Gediminas Technical University
Objective(s) of a study program: To prepare specialists of biomathematics (masters in mathematical modelling) who have appropriate knowledge and skills for creating mathematical models of complicated biosystems, for analyzing data coming form this kind of systems, for using various problem-oriented informational technologies. The biosystems modelling masters will be able to use their knowledge and skills for formulating and solving real-life problems in biology, biotechnology, pharmacy, medicine and ecology. Learning outcomes: Knowledge and its applications: A1 Knowing the principles of mathematical modeling and possibilities of its application in biology and medicine; A2 Knowing and understanding the specifics of modelling and analysis of molecular systems; A3 Knowing and understanding statistical data analysis methods for biology and medicine, and survival analysis methods; A4 Knowing and understanding human physiological systems and biophysics; Abilities of doing research: B1 Being able to analyze various real world processes, to create, improve and assess mathematical models for solving problems in mathematics and biology; B2 Being able to choose and apply appropriate mathematical models for given biosystems; B3 Being able to find and synthesize information during the whole problem solving process; B4 Being able to analyze, interpret, compare and assess the results of modeling, select the optimal solutions, formulate and justify the conclusions, make forecasts; Special abilities: C1 Being able to constru ...
Provider NameKaunas University of Technology
Objective(s) of a study programme: To prepare qualified specialists: with deepen knowledge in mathematics, computer science and business, enabling possibility to analyse business big data; able to identify at conceptual level the business issues in traditional and global organizations based on networking, to creatively apply the acquired knowledge in new situations, to develop mathematical models for relevant business decision-making, to critically evaluate data and results, as well as able to communicate information for audience of specialists, to work in a team and to continually develop their professionalism. Learning outcomes: Knowledge and its application A1. Demonstrate deepened and expanded math knowledge related to process and event analysis, prognosis, optimization, risk assessment and big data. A2. Have knowledge of business organizations’ operational processes, efficiency indicators, modelling principles, factors influencing decision-making, and able to use them for development of mathematical models. A3. Have knowledge of specification of enterprise informational needs, purpose of metadata, importance of big data management in the organization, and able to use databases, to create and use metadata, to specify user needs and limitations of the information system. A4. Have knowledge of mathematical methods applied to the development of analysis models for business big data, understand the analysis phases and their performance method, and able to apply it in the interdisciplinary area. A5. Have knowled ...
Provider NameKaunas University of Technology
Future holders of a master’s degree in statistics study econometrics, asymptotic statistics, microeconomic analysis, financial econometrics, multidimensional statistics, etc. Professional training is not planned. This econometrics programme is intended for individuals who have acquired a bachelor’s degree in econometrics, mathematics, economics, statistics, or physics and would like to earn a master’s degree in statistics. ...
Provider NameVilnius University
Aim(s) of a study programme: To develop the students’ ability in econometric modelling, providing the students with knowledge of modern statistics and economics, which will be useful in data collecting, systemizing, analysing and interpretation and understanding economic processes. To teach students applications of statistical methods in economics, finance and other areas related with uncertainty; critically evaluate statistical information and to explain it to the experts; to work individually and in team, constantly raise the level of knowledge. Learning outcomes: 1. collect, analyse and interpret information independently, develop ideas and argue critically them; 2. apply the knowledge obtained in economics and statistics in the development of the econometric projects; 3. apply specialized computer programs (R, EVIEWS, GRETL) for data analysis; 4. understand and to explain to others the importance of statistical information and the relevance in modern world; 5. choose an appropriate statistical test for hypothesis testing; 6. make linear regression models, structural and reduced vector models, estimate their parameters, test hypothesis for parameters, interpret the results obtained and to apply these results in practice; 7. apply time series models (ARIMA, GARCH, VECM) for real data, estimate their parameters, interpret the results obtained and to apply those models in practice; 8. know the principles, concepts and models of microeconomics and macroeconomics; 9. understand economic processes and be able cri ...
Provider NameVilnius University