| Language of instruction : English |
| | | Exam contract: not possible |
|
Sequentiality
|
| |
|
No sequentiality
|
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 | P1 SBU | P1 SP | 2nd Chance Exam1 | Tolerance2 | Final grade3 | |
 | 1st year Master Bioinformatics | Compulsory | 135 | 5,0 | 135 | 5,0 | Yes | No | Numerical |  |
| 1st year Master Bioinformatics - icp | Compulsory | 135 | 5,0 | 135 | 5,0 | Yes | No | Numerical | |
| 1st year Master Biostatistics | Compulsory | 135 | 5,0 | 135 | 5,0 | Yes | No | Numerical | |
| 1st year Master Biostatistics - icp | Compulsory | 135 | 5,0 | 135 | 5,0 | Yes | No | Numerical | |
| 1st year Master Data Science | Compulsory | 135 | 5,0 | 135 | 5,0 | Yes | No | Numerical | |
| 1st year Quantitative Epidemiology | Compulsory | 135 | 5,0 | 135 | 5,0 | Yes | No | Numerical | |
| 1st year Master Quantitative Epidemiology - icp | Compulsory | 135 | 5,0 | 135 | 5,0 | Yes | No | Numerical | |
|
| | | Learning outcomes |
- EC
| The student is capable of acquiring new knowledge. |
|
| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
|
|
In this course, we deal with the following topics:
- Descriptive statistics:
- different types of variables
- measures of centrality
- measures of variability
- measures of relative standing
- graphical methods to present data
- Basic probability theory:
- sample space, events, probability, combinatorics
- Law of total probability, Bayes rule
- stochastic variables, (joint, conditional) distributions, (conditional) expectations
- transformation of distributions
- Law of large numbers, Central limit theorem
- generating samples from a population
- Statistical inference:
- Confidence intervals: CI for mean(s), CI for proportion(s), CI for variance(s)
- hypothesis testing: null-hypothesis, alternative hypothesis, test-statistic, critical value, p-value
- hypothesis for mean, proportion and variance
- comparing means, proportions, variances
- Introduction to estimation methods: maximum likelihood, methods of moments, least squares method
|
|
|
|
|
|
|
|
|
Collective feedback moment ✔
|
|
|
|
Lecture ✔
|
|
|
|
|
|
|
|
Exercises ✔
|
|
|
|
Period 1 Credits 5,00
| Evaluation method | |
|
| Written evaluaton during teaching periode | 10 % |
|
|
|
|
|
Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
|
|
|
| Compulsory textbooks (bookshop) |
| |
[Mathematical Statistics and Data Analysis],[John A. Rice],[Third Edition],[Cengage],[9780495118688],[] |
|
|
| Compulsory course material |
| |
Lecture notes for the lectures will be provided by the lecturer through the electronic platform. |
|
|
|
|
|
| Exchange Programme Statistics | Optional | 135 | 5,0 | 135 | 5,0 | Yes | Yes | Numerical | |
|
| |
|
|
In this course, we deal with the following topics:
- Descriptive statistics:
- different types of variables
- measures of centrality
- measures of variability
- measures of relative standing
- graphical methods to present data
- Basic probability theory:
- sample space, events, probability, combinatorics
- Law of total probability, Bayes rule
- stochastic variables, (joint, conditional) distributions, (conditional) expectations
- transformation of distributions
- Law of large numbers, Central limit theorem
- generating samples from a population
- Statistical inference:
- Confidence intervals: CI for mean(s), CI for proportion(s), CI for variance(s)
- hypothesis testing: null-hypothesis, alternative hypothesis, test-statistic, critical value, p-value
- hypothesis for mean, proportion and variance
- comparing means, proportions, variances
- Introduction to estimation methods: maximum likelihood, methods of moments, least squares method
|
|
|
|
|
|
|
|
|
Collective feedback moment ✔
|
|
|
|
Lecture ✔
|
|
|
|
|
|
|
|
Exercises ✔
|
|
|
|
Period 1 Credits 5,00
| Evaluation method | |
|
| Written evaluaton during teaching periode | 10 % |
|
|
|
|
|
Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
|
|
|
| Compulsory textbooks (bookshop) |
| |
[Mathematical Statistics and Data Analysis],[John A. Rice],[Third Edition],[Cengage],[9780495118688],[] |
|
|
| Compulsory course material |
| |
Lecture notes for the lectures will be provided by the lecturer through the electronic platform. |
|
|
|
|
|
1 examination regulations art.1.3, section 4. |
| 2 examination regulations art.4.7, section 2. |
3 examination regulations art.2.2, section 3.
|
| Legend |
| SBU : course load | SP : ECTS | N : Dutch | E : English |
|