| Language of instruction : English |
| | | Exam contract: not possible |
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Sequentiality
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No sequentiality
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There is no data for this choice.
Change the language, year or choose another item in the dropdown list if it is available.
| Degree programme | | Study hours | Credits | P2 SBU | P2 SP | 2nd Chance Exam1 | Tolerance2 | Final grade3 | |
 | 1st year Master Bioinformatics - icp | Compulsory | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical |  |
| 1st year Master Biostatistics - icp | Compulsory | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
| 1st year Master Quantitative Epidemiology - icp | 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. | | | - DC
| ... correctly using state-of-the-art design methodology. | - EC
| The student is capable of acquiring new knowledge. | - EC
| The student can critically appraise methodology and challenge proposals for and reported results of data analysis. | - EC
| The student can work in a multidisciplinary, intercultural, and international team. | - EC
| The student knows the international nature of the field of statistical science and data science. | - EC
| The student knows the societal relevance of statistics and data science. | - EC
| The student knows the relevant stakeholders and understands the need for assertive and empathic interaction with them. |
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| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
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Designing of Agricultural Experiments:
- General aspects and considerations
- Completely Randomized Design (CRD)
- Randomized Complete Block Design (RCBD)
- Latin squares designs (LS)
- Incomplete block design (IBD)
- Split plot design (SPD)
- Statistical analysis of experimental designs
- Factorial and Nested designs
- On farm trials
- Inter-cropping
- Research methods complexities
This course is organised in cooperation with lecturers from our South partners.
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Period 2 Credits 4,00 Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
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| Compulsory course material |
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Handouts by the instructor. |
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| 1st year Master Bioinformatics | Optional | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
| 1st year Master Biostatistics | Optional | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
| 1st year Master Data Science | Optional | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
| 1st year Quantitative Epidemiology | Optional | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
| Exchange Programme Statistics | Optional | 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. | | | - DC
| ... correctly using state-of-the-art design methodology. | - EC
| The student is capable of acquiring new knowledge. | - EC
| The student can critically appraise methodology and challenge proposals for and reported results of data analysis. | - EC
| The student can work in a multidisciplinary, intercultural, and international team. | - EC
| The student knows the international nature of the field of statistical science and data science. | - EC
| The student knows the societal relevance of statistics and data science. | - EC
| The student knows the relevant stakeholders and understands the need for assertive and empathic interaction with them. |
|
| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
|
|
Designing of Agricultural Experiments:
- General aspects and considerations
- Completely Randomized Design (CRD)
- Randomized Complete Block Design (RCBD)
- Latin squares designs (LS)
- Incomplete block design (IBD)
- Split plot design (SPD)
- Statistical analysis of experimental designs
- Factorial and Nested designs
- On farm trials
- Inter-cropping
- Research methods complexities
This course is organised in cooperation with lecturers from our South partners.
|
|
|
Period 2 Credits 4,00 Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
|
|
|
| Compulsory course material |
| |
Handouts by the instructor. |
|
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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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