Project: Multivariate and Hierarchical Data (3565) |
| Credits: 8,0 | | Study load hours: 216 | Period: semester 2 (8sp)  |
| Language of instruction: English | | Exam contract: not possible |
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Contents "Multivariate and Hierarchical Data": - Repeated measures - Clustered data - Multivariate methods. Contents "Discovering Associations": - Sample size calculations - Statistical research for pharmaceutical research and development - Ethical aspects of consulting, reporting - Statistical consulting training & protocol for the design of experiments
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| Compulsory course material |
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All course material is made available through BlackBoard, by the lecturers. |
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Distance learning ✔
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Lecture ✔
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Project ✔
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Small group session ✔
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Semester 2 (8,00sp)
| Evaluation method | |
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| Written evaluation during teaching period | 40 % |
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| Oral evaluation during teaching period | 5 % |
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| Evaluation conditions (participation and/or pass) | ✔ |
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| Conditions | All components have to be taken up. |
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| Consequences | Students get an X score if they do not meet the condition. |
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| Additional information | Note: For the oral part of the exam, the range is [-4;+5]. This penalizes an imbalance between good reports and poor individual performance. |
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Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
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| Explanation (English) | The assignment for the second chance exam remains the same. The
structure of the oral exam for the second chance remains the same. |
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Learning outcomes | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
Master of Statistics and Data Science
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- 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. | | | - DC
| ... correctly using state-of-the-art software. | - 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 is an effective written and oral communicator, both within their own field as well as across disciplines. | | | - DC
| The student is an effective writer in their own field. | | | - DC
| The student is an effective oral communicator, both within their own field as well as across disciplines. | | | - DC
| The student is an effective writer, both within their own field as well as across disciplines. | | | - DC
| The student is an effective oral communicator in their own field. | - EC
| The student is capable of acquiring new knowledge. |
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| Included in these programmes | Tolerance3 |
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1st year Master Bioinformatics
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N
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1st year Master Biostatistics
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N
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1st year Master Data Science
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N
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1st year Quantitative Epidemiology
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N
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Exchange Programme Statistics
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Y
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1 Education, Examination and Legal Position Regulations art.12.2, section 2. |
| 2 Education, Examination and Legal Position Regulations art.15.1, section 3. |
3 Education, Examination and Legal Position Regulations art.16.9, section 2.
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