Deildarforseti:Dr. Jón Þór Sturluson
BSc í viðskiptafræði
FagréttindiBSc í viðskiptafræði
Skyldufag á brautKennslutungumál
Valfag á brautUndanfarar fyrir námskeið
Haustönn/Fall 2022
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Nánari upplýsingarGreining og hönnun hugbúnaðarValnámskeiðT-216-GHOH6 Einingar
Nánari upplýsingarHugbúnaðarfræðiValnámskeiðT-303-HUGB6 Einingar
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Nánari upplýsingarReikningshaldSkyldaV-108-REHA6 Einingar
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Nánari upplýsingarHagrannsóknir IValnámskeiðV-210-ECON6 Einingar
Nánari upplýsingarGerð og greining ársreikningaSkyldaV-307-GARS6 Einingar
Nánari upplýsingarAlþjóðaviðskiptiSkyldaV-308-ALVI6 Einingar
Nánari upplýsingarApplied Game TheoryValnámskeiðV-332-AGTH6 Einingar
Nánari upplýsingarSaga hagfræðikenninga og hagrænnar hugsunarValnámskeiðV-341-ETET6 Einingar
Nánari upplýsingarHagnýt tölfræði IISkyldaV-406-TOL26 Einingar
1. árPrenta
ÖnnHaustönn/Fall 2022
Stig námsgreinar3. Grunnnám, sérhæft námskeið
Tegund námskeiðsSkylda
UndanfararV-303-TOL1, Hagnýt tölfræði I
SkipulagFjórir tímar á viku, fyrirlestrar og dæmatímar.
Enginn skráður kennari.
The course focuses on a study of linear regression, the theory behind and the application of the method. Part 1 of the course covers simple and multiple regressions which are used in the analysis of cross-sectional data. Part 2 introduces basic time series models. Examples of simple economic applications are used throughout the course. Students use SPSS. License to use SPSS can be purchased at the reception desk in Sólin. During the course students will get some guidance on how to use the program. However, it has to be noted that this statistical program is only the means to an end – the course’s aim is not to thoroughly teach how to use SPSS, 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.
  • 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).
  • 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 will be the program used in class) (S4).
  • 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 and evaluate simple research papers that use these methods (C3),
  • Be able to present the research results in a comprehensible and brief way (C4).

Ekkert skráð lesefni.
Lectures will take place twice a week (Wednesdays and Fridays). Wednesdays’ lectures will be organized as typical lectures where teacher presents material and relevant examples. Most of the content of Wednesdays´ lectures will be available on slides that will be uploaded on Wednesdays mornings. However, there will be additional examples that will be solved on the board and they will not be part of slides. Students are required to take notes.Fridays’ lectures will be organized as problem solving sessions (called Exercise Session in the Study Plan). Students will be presented with a number of exercises covering material discussed in class and they will be required to work on those during the class. It is advisable that students bring the book and lecture notes to these sessions. In total, there will be eight Exercise Sessions. After the end of the class each student is required to submit an answer sheet/Exercise Session Report to the teacher. The precise way of sending the report will be explained later in the class. These reports will only receive grade of Pass+, Pass or Fail. In order to get Pass+ all answers have to be correct, in order to pass (receive Pass) more than 50% of the answers need to be correct.The detailed schedule can be found in this document. Please be aware that it might be prone to changes and updates during the semester.The course does not require much learning by heart. Instead it relies heavily on your ability to understand the topics covered and your ability to use relevant methods where needed. To acquire that level of knowledge, skills and competences requires that you take an active role in your studies throughout the course.The assignments in the textbook, material covered in lectures and assignments for problem solving sessions will be equally covered in the final.TA classes:Once a week there will be problem solving sessions with a Teaching Assistant (TA). They will start in the second week of the course. Please prepare for the TA sessions. This means: try solving assigned exercises before the class takes place. Most students learn the most when they prepare before-hand and check their solutions with the solutions given by the TA.
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