| Language of instruction : English |
| Exam contract: not possible |
| Degree programme | | Study hours | Credits | P2 SBU | P2 SP | 2nd Chance Exam1 | Tolerance2 | Final grade3 | |
 | 1st year Master Biostatistics - distance learning | Compulsory | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical |  |
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| | | Learning outcomes |
- EC
| The student can handle scientific quantitative research questions, independently, effectively, creatively, and correctly using state-of-the-art design and analysis methodology and software. | | | - DC
| ... correctly using state-of-the-art analysis methodology. | - EC
| The student is capable of acquiring new knowledge. | - EC
| The student can put research and consulting aspects of one or more statistical fields into practice. | - EC
| The student is able to correctly use the theory, either methodologically or in an application context or both, thus contributing to scientific research within the field of statistical science, data science, or within the field of application. | | | - DC
| The student is able to correctly use the theory in an application context, thus contributing to scientific research within the field of application. |
|
| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
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The course focuses on rank test statistic. We will discuss rank test statistics for comparing two independent groups, two dependent groups, and the comparison of more than two independent and dependent groups.
The course requires knowledge of concepts in statistical inference as introduced in the course Concepts of Probability and Statistics. The statistical software used is mainly R. Thus, ideally students should also have followed the course Statistical Software.
At the end of the course, the student should be able to decide on the appropriate rank test to be used for a range of real life examples, to be able execute the test and to interpret the results.
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Period 2 Credits 4,00
| Evaluation method | |
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| Written exam | 100 % |
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| Multiple-choice questions | ✔ |
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| Use of study material during evaluation | ✔ |
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| Explanation (English) | All course material can be used |
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Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
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| Prerequisites |
| |
The student should be familiar with basic concepts of statistics; such as type I and type II error, hypothesis testing, pvalue, and power. |
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| Compulsory textbooks (bookshop) |
| |
Nonparametrics Statistical Methods based on Ranks. E.L. Lehmann and H.J.M. D'Abrera. 9780387352121 |
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| Compulsory course material |
| |
Nonparametrics, Statistical Methods based on Ranks., E.L. Lehmann and H.J.M. D'Abrera |
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|
| Recommended reading |
| |
Nonparametrics: Statistical Methods Based on Ranks,Erich L. Lehmann; H.J.M. D'Abrera,Springer,9780387352121 |
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| 1st year Master Bioinformatics - distance learning | Optional | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
| 1st year Master Quantitative Epidemiology - distance learning | Optional | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
|
| | | Learning outcomes |
- EC
| The student can handle scientific quantitative research questions, independently, effectively, creatively, and correctly using state-of-the-art design and analysis methodology and software. | | | - DC
| ... correctly using state-of-the-art analysis methodology. | - EC
| The student is capable of acquiring new knowledge. | - EC
| The student can put research and consulting aspects of one or more statistical fields into practice. | - EC
| The student is able to correctly use the theory, either methodologically or in an application context or both, thus contributing to scientific research within the field of statistical science, data science, or within the field of application. | | | - DC
| The student is able to correctly use the theory in an application context, thus contributing to scientific research within the field of application. |
|
| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
|
|
The course focuses on rank test statistic. We will discuss rank test statistics for comparing two independent groups, two dependent groups, and the comparison of more than two independent and dependent groups.
The course requires knowledge of concepts in statistical inference as introduced in the course Concepts of Probability and Statistics. The statistical software used is mainly R. Thus, ideally students should also have followed the course Programming in R.
At the end of the course, the student should be able to decide on the appropriate rank test to be used for a range of real life examples, to be able execute the test and to interpret the results.
|
|
|
Period 2 Credits 4,00
| Evaluation method | |
|
| Written exam | 100 % |
|
|
| Multiple-choice questions | ✔ |
|
|
|
|
|
|
| Use of study material during evaluation | ✔ |
|
| Explanation (English) | All course material is allowed to be used |
|
|
|
Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
|
|
|
| Prerequisites |
| |
The student should be familiar with basic concepts of statistics; such as type I and type II error, hypothesis testing, pvalue, and power. |
|
|
| Compulsory textbooks (bookshop) |
| |
Nonparametrics Statistical Methods based on Ranks. E.L. Lehmann and H.J.M. D'Abrera. 9780387352121 |
|
|
| Compulsory course material |
| |
Nonparametrics, Statistical Methods based on Ranks., E.L. Lehmann and H.J.M. D'Abrera |
|
|
| Recommended reading |
| |
Nonparametrics: Statistical Methods Based on Ranks,Erich L. Lehmann; H.J.M. D'Abrera,Springer,9780387352121 |
|
|
|
|
|
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 |
|