| Language of instruction : English |
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Sequentiality
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Mandatory sequentiality bound on the level of programme components
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For following programme components you must have acquired a credit certificate, exemption, already tolerated unsatisfactory grade or selected tolerable unsatisfactory grade.
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Statistics for economists 1 (3509)
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3,0 stptn |
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Statistics for economists 2 (3719)
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6,0 stptn |
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| Degree programme | | Study hours | Credits | P1 SBU | P1 SP | 2nd Chance Exam1 | Tolerance2 | Final grade3 | |
 | 3rd Bachelor of Business Economics | Compulsory | 81 | 3,0 | 81 | 3,0 | Yes | Yes | Numerical |  |
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| | | Learning outcomes |
- EC
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The holder of the degree works in a team with a view to a multidisciplinary approach to a business problem. (Teamwork)
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| The holder of the degree communicates in a business context in writing and orally, and if necessary with visual support. (Communication) | - EC
| The holder of the degree selects and implements scientific research methods under supervision. (Research skills) | - EC
| The holder of the degree analyses, interprets, evaluates and reports research results under supervision. (Research skills) | - EC
| The holder of the degree is able to take a conceptual and analytical approach to strategic policy issues, drawing on business conceptual frameworks. (Problem-solving capacity) |
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| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
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The student will become familiar with key concepts in "Econometrics". An important aspect of the course is also "application", that is, key concepts will be tested with real data and applied to economic topics. The following topics will be handled in the course:
- Linear Regression with multiple variables: Omitted variable bias, multiple regression model, multicollinearity
- Hypothesis testing and confidence intervals: Joint hypothesis testing, F-statistics, testing linear restrictions
- Non-linear regression analysis: Non-linear regression function, log-linear models, interaction terms, non-linear least squares estimator
- Panel data regression analysis: Fixed effects, OLS dummy approach (with reservation)
- Regression with a binary dependent variable: Linear probability model, probit, logit, maximum likelihood estimation (with reservation)
- Empirical application(s) of the above concepts in SPSS
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Lecture ✔
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Response lecture ✔
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Small group session ✔
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Period 1 Credits 3,00 Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
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| Prerequisites |
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Basics in mathematics (derivatives, functions, transformations) and statistics (probabilities, distributions, anova, hypothesis testing).
Chapter 4 and 5 of Stock and Watson tackles univariate regression analysis and should already be known at the start of the course. At the start of this course, these materials will be refreshed during the first lecture. |
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| Compulsory textbooks (bookshop) |
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Introduction to Econometrics,Stock, J.H. and M.M. Watson,4th Edition,Pearson |
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| Compulsory course material |
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*Lecture slides
*Companion website of the S&W textbook
*Testbank
*Solution of exercises and empirical exercises
*Additional lecture materials posted on BB
*SPSS manual |
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| Bridging Programme Master of Business Economics | Compulsory | 81 | 3,0 | 81 | 3,0 | Yes | Yes | Numerical | |
| Preparation Programme Master of Business Economics | Compulsory | 81 | 3,0 | 81 | 3,0 | Yes | Yes | Numerical | |
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The student will become familiar with key concepts in "Econometrics". An important aspect of the course is also "application", that is, key concepts will be tested with real data and applied to economic topics. The following topics will be handled in the course:
- Linear Regression with multiple variables: Omitted variable bias, multiple regression model, multicollinearity
- Hypothesis testing and confidence intervals: Joint hypothesis testing, F-statistics, testing linear restrictions
- Non-linear regression analysis: Non-linear regression function, log-linear models, interaction terms, non-linear least squares estimator
- Panel data regression analysis: Fixed effects, OLS dummy approach (with reservation)
- Regression with a binary dependent variable: Linear probability model, probit, logit, maximum likelihood estimation (with reservation)
- Empirical application(s) of the above concepts in SPSS
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Lecture ✔
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Response lecture ✔
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|
|
|
Small group session ✔
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|
|
|
Period 1 Credits 3,00 Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
|
|
|
| Prerequisites |
| |
Basics in mathematics (derivatives, functions, transformations) and statistics (probabilities, distributions, anova, hypothesis testing).
Chapter 4 and 5 of Stock and Watson tackles univariate regression analysis and should already be known at the start of the course. At the start of this course, these materials will be refreshed during the first lecture. |
|
|
| Compulsory textbooks (bookshop) |
| |
Introduction to Econometrics,Stock, J.H. and M.M. Watson,4th Edition,Pearson |
|
|
| Compulsory course material |
| |
*Lecture slides
*Companion website of the S&W textbook
*Testbank
*Solution of exercises and empirical exercises
*Additional lecture materials posted on BB
*SPSS manual |
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| Exchange Programme Business Economics | Optional | 81 | 3,0 | 81 | 3,0 | Yes | Yes | Numerical | |
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| |
|
|
The student will become familiar with key concepts in "Econometrics". An important aspect of the course is also "application", that is, key concepts will be tested with real data and applied to economic topics. The following topics will be handled in the course:
- Linear Regression with multiple variables: Omitted variable bias, multiple regression model, multicollinearity
- Hypothesis testing and confidence intervals: Joint hypothesis testing, F-statistics, testing linear restrictions
- Non-linear regression analysis: Non-linear regression function, log-linear models, interaction terms, non-linear least squares estimator
- Panel data regression analysis: Fixed effects, OLS dummy approach (with reservation)
- Regression with a binary dependent variable: Linear probability model, probit, logit, maximum likelihood estimation (with reservation)
- Empirical application(s) of the above concepts in SPSS
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|
|
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|
|
Lecture ✔
|
|
|
|
Response lecture ✔
|
|
|
|
Small group session ✔
|
|
|
|
Period 1 Credits 3,00 Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
|
|
|
| Prerequisites |
| |
Basics in mathematics (derivatives, functions, transformations) and statistics (probabilities, distributions, anova, hypothesis testing).
Chapter 4 and 5 of Stock and Watson tackles univariate regression analysis and should already be known at the start of the course. At the start of this course, these materials will be refreshed during the first lecture. |
|
|
| Compulsory textbooks (bookshop) |
| |
Introduction to Econometrics,Stock, J.H. and M.M. Watson,4th Edition,Pearson |
|
|
| Compulsory course material |
| |
*Lecture slides
*Companion website of the S&W textbook
*Testbank
*Solution of exercises and empirical exercises
*Additional lecture materials posted on BB
*SPSS manual |
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1 examination regulations art.1.3, section 4. |
| 2 examination regulations art.4.7, section 2. |
3 examination regulations art.2.2, section 3.
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| Legend |
| SBU : course load | SP : ECTS | N : Dutch | E : English |
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