Viðskiptadeild
Deildarforseti:Dr. Friðrik Már Baldursson
Vefpóstur:vd@ru.is
Vefsíða:http://www.ru.is/vd
KennararSkoða
BSc í hagfræði og fjármálum
Annir:6
Ár:3
Einingar:180
HæfniviðmiðSkoða
FagréttindiBSc í hagfræði og fjármálum
Táknmyndir
Skyldufag á brautKennslutungumál
Valfag á brautUndanfarar fyrir námskeið
Prenta
Haustönn/Fall 2020
Nánari upplýsingarÞjóðhagfræðiSkyldaV-103-THAG6 Einingar
Nánari upplýsingarHagnýt stærðfræði ISkyldaV-104-STÆR6 Einingar
Nánari upplýsingarMarkaðsfræði ISkyldaV-105-MAR16 Einingar
Nánari upplýsingarFjármál fyrirtækjaSkyldaV-107-FJAR6 Einingar
Nánari upplýsingarReikningshaldSkyldaV-108-REHA6 Einingar
Nánari upplýsingarÞjóðhagfræði IISkyldaV-204-THII6 Einingar
Nánari upplýsingarHagrannsóknir ISkyldaV-210-ECON6 Einingar
Ár
1. árPrenta
ÖnnHaustönn/Fall 2020
Stig námskeiðsÓskilgreint
Tegund námskeiðsValnámskeið
UndanfararV-103-THAG, Þjóðhagfræði
V-104-STÆR, Hagnýt stærðfræði I
V-201-RHAG, Rekstrarhagfræði I
V-303-TOL1, Hagnýt tölfræði I
SkipulagEkkert skráð skipulag.
Kennari
Ewa Ryszarda Lazarczyk Carlson
Lýsing
  The course is divided into two parts. Part 1 covers simple and multiple regressions which are used in the analysis of cross-sectional data. Part 2 discusses basic time series models. The course uses algebra and some basic differential calculus. Matrix algebra is also used when appropriate and useful. Examples of simple economic applications are used throughout the course. Students use SPSS for the first part of the course and R for the second part. License to use SPSS can be purchased at the reception desk in Sólin. It is crucial that you get SPSS as soon as possible, as already in the second week of the course we will be using it! R is a programing language that can be downloaded for free from https://www.r-project.org (Links to an external site.)Links to an external site.. During the course students will get some guidance on how to use both programs. However, it has to be noted that these statistical programs are only the means to an end – the course’s aim is not to thoroughly teach how to use these programs, it is to be able to perform the chosen analysis with the use of the computer software and primarily to understand the results and be able to judge the adequacy of the model and its fit to data.
Námsmarkmið
Learning outcomes: The learning outcomes outline the factors that fall under the heading of knowledge, skills and competences within Econometrics that students are expected to acquire during the semester. Each outcome is coded with a letter-number combination that is used in the Study Plan (Learning Outcomes column) to indicate which Lecture aims to fulfil which factor.   Knowledge: Students should know the basic econometric methods to handle cross-sectional data and time-series. These include:
  • The method of linear regression (K1),
  • Assumptions necessary to perform regression analysis (K2),
  • Basic test necessary to verify the fit of the model (K3),
  • Interpretation of the results (K4),
  • Basic time series methods (K5).
  •   Skills: Students should know how to use econometric methods to analyze data. That means that students should be able to:
  • Choose the appropriate method for the data at hand (S1),
  • Use it to analyze the data (S2),
  • Interpret the results (S3).
  • Students should become familiar with using a chosen statistical package (SPSS and R will be the programs used in class) (S4).
  •   Competences:
  • Students should be able to use econometric models for decision-making (C1),
  • Be able to judge the adequacy of the method used for analysis (C2),
  • Be able to read simple research papers that use these methods (C3),
  • Be able to present the research results in a comprehensible and brief way (C4).
  • Námsmat
    Ekkert skráð námsmat.
    Lesefni
    Ekkert skráð lesefni.
    Kennsluaðferðir
     A large part, although not all, of the topics will be covered in lectures, while students are also expected to study the topics in the textbook. In problem solving sessions students will apply the knowledge introduced in lectures and covered in the textbook. Make sure you prepare for lectures and problem solving-sessions (TA classes) and follow through by reading the textbook and come prepared for class. The lectures will largely follow the study plan below and the assignments will be posted for the TA sessions.
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