Lectures:
1. Introduction to Time Series Models.
2. Stationary and Non-stationary Stochastic Processes. Seasonality.
3. Stationarity. Testing for Stationarity.
4. ARIMA Models. ARCH Models.
5. Cointegration. Testing for Contegration. Error Correction Models.
Computer Classes:
Application of Dynamic Econometric Methods in Modelling Financial Time Series with the Use of Computer Tools: MS Excel and GRETL.
Learning outcomes:
Knowledge:
knowledge of dynamic econometric models and methods.
Competence and skills:
data analysis, applications of dynamic econometric methods in modelling financial time series using software (MS Excel and GRETL).
Contact person:
Prof. Józef Dziechciarz, Mgr Anna Król
Literature:
[1] Enders W.: Applied Econometric Time Series, John Wiley & Sons 2010.
[2] Taylor S.: Modelling Financial Time Series, John Wiley & Sons 1992.
[3] Brooks Ch.: Introductory Econometrics for Finance, Cambridge University Press 2002.
[4] Mills T. C., Markellos R. N.: The Econometric Modelling of Financial Time Series, Cambridge University Press 2008.
[5] Greene W.H.: Econometric Analysis, Prentice Hall 1999.
Faculty:
All Faculties
Is this a copy of the lecture already taught on UE?
yes
title: Ekonometria dynamiczna i finansowa
department: ZIF
faculty: IiE
specialty: all
year: 1 (MS)
Lectures:
1. Simple Regression Model. Ordinary Least Squares (OLS) Estimation. Assumptions Underlying Classical Linear Regression Model.
2. Multiple Regression Model. Properties of the OLS Estimators.
3. Goodness of Fit. Hypothesis Testing: t-test, F-test. Normality of the Disturbance Term.
4. Heteroskedasticity. Autocorrelation.
5. Specification Analysis and Model Selection. Multicollinearity. Computer Classes:
Application of Econometric Methods in Economics, Finance and Business with the Use of Computer Tools: MS Excel and GRETL.
Learning outcomes:
Knowledge:
basic knowledge of econometric theory, models and methods
Competence and skills:
data analysis, techniques of econometric models' estimation and verification (on the basic level))
Contact person:
Prof. Józef Dziechciarz, Mgr Anna Król
Literature:
[1] Maddala G.S.: Introduction to Econometrics, John Wiley & Sons 2001.
[2] Dougherty Ch.: Introduction to Econometrics, Oxford University Press 2002.
[3] Greene W.H.: Econometric Analysis, Prentice Hall 1999.
[4] Davidson R., MacKinnon J.G.: Econometric Theory and Methods, Oxford University Press 2004.
[5] Brooks Ch.: Introductory Econometrics for Finance, Cambridge University Press 2002.
Faculty:
All Faculties
Is this a copy of the lecture already taught on UE?
yes
title: Ekonometria
department: ZIF
faculty: FIR, IiE
specialty: all
year: 2 (LS)
Lectures:
1. Introduction to Marketing Research, Research Design, Data Collection and Analysis.
2. Measurement and Scaling, Data Preparation.
3. Analysis of Variance and Covariance, Correlation and Regression.
4. Factor Analysis, Cluster Analysis, Multidimensional Scaling, Conjoint Analysis.
5. Writing Marketing Research Report.
Computer Classes:
Application of Marketing Research Methods with the Use of Computer Tools: MS Excel and Statistica.
Learning outcomes:
Knowledge:
basic knowledge of marketing research theory and methods.
Competence and skills:
mastering marketing research methods and techniques using software (MS Excel and Statistica).
Contact person:
Dr Klaudia Przybysz
Literature:
[1] Churchill G.A. Jr.: Marketing Research: Methodological Foundations, Dryden Press 1995.
[2] Zikmund W. G.: Exploring Marketing Research, Dryden Press 1994.
[3] Anderson T. W., Finn J. D.: The New Statistical Analysis of Data, Springer-Verlag 1997.
[4] Malhotra N. K., Birks D. F.: Marketing Research : an Applied Approach, Prentice Hall 1999.
[5] Webb J. R.: Understanding and Designing Marketing Research, Academic Press 1992.
Faculty:
All Faculties
Is this a copy of the lecture already taught on UE?
yes
title: Badania marketingowe
department: ZIF
faculty: Z
specialty: all
year: 3 (LS)
Lectures:
1. Research Design (Research Topic, Data Sources, Sample Selection, Literature Review, Ethical Aspects).
2. Basic Data Analysis (Measurement Scales, Descriptive Statistics, Correlation Analysis, Regression Analysis, Hypothesis Testing and Inference).
3. Advanced Data Analysis and Special Topics (Classification Trees, Clustering Analysis, Binary Choice Models).
4. Writing Research Report (Report Structure, Theoretical Introduction, Data Presentation, Results Presentation, Graphs and Plots, References).
5. Presentation of the Results (Preparing Presentation, Effective Presentation Techniques). Computer Classes:
Conducting Data Analyses with the Use of Computer Tools: MS Excel and Statistica. Preparing Presentation of the Research Results using Computer Tools: MS Power Point or Latex Beamer Class.
Learning outcomes:
Knowledge:
basic knowledge of research design and data analysis methods.
Competence and skills:
designing economic research, mastering data analysis methods and techniques using software (MS Excel, Statistica), preparing presentations of the results using software (MS Power Point or Latex Beamer Class).
Contact person:
Dr Klaudia Przybysz
Literature:
[1] Anderson T. W., Finn J. D.: The New Statistical Analysis of Data, Springer-Verlag 1997.
[2] Kumar R.: Research Methodology, SAGE Publications 2005.
[3] Warner R.M.: Applied Statistics, Sage 2008.
[4] Gnanadesikan R.: Methods for Statistical Data Analysis of Multivariate Observations, John Wiley & Sons 1997.
[5] Maddala G.S.: Introduction to Econometrics, John Wiley & Sons 2001.
Faculty:
All Faculties
Is this a copy of the lecture already taught on UE?
yes
title: Metody analizy danych
department: ZIF
faculty: Z
specialty: all
year: 2 (LS)
