### General Information

Course Code | E_EOR1_PT |
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Credits | 6 EC |

Period | P1+2 |

Course Level | 100 |

Language of Tuition | English |

Faculty | School of Business and Economics |

Course Coordinator | dr. D.A. van der Laan |

Examiner | dr. D.A. van der Laan |

Teaching Staff |
dr. D.A. van der Laan prof. dr. B.F. Heidergott |

### Practical Information

You need to register for this course yourself

Teaching Methods | Study Group, Lecture |
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Target audiences

This course is also available as:

### Course Objective

The learning objectives are as follows:1. Knowledge and understanding of basic concepts of probability theory

and probability distributions.

2. Selecting an appropriate method to solve typical problems in

probability theory and applying these methods correctly.

3. Translating verbally described problems in the language of

probability theory to solve the problem.

4. Knowledge of probability distributions which occur most commonly in

practice and being able to use the known properties of these

distributions to solve problems.

### Course Content

The mathematical foundation for both modeling decisions underuncertainty when performing statistics is the probability and the

probability therefore has a central role in the bachelor Econometrics

and Operations Research.

The structure of this course is as follows.

• Basic elements of the probability account

(random experiment, outcomes space, eventuality and opportunity) and

fundamental calculation rules for opportunities on eventualities.

Combinatorial probability models, conditional probabilities, the rule of

Bayes, and the law of total probability.

• Introduction of the concept of a stochastic variable, and

concepts such as distribution function, probability function,

expectation and

variance of a stochastic variable.

• Specific discrete probability distributions, such as the

binomial, hypergeometric, Poisson, and geometric distribution.

• Continuous stochastic variables and associated probability

distributions. Specific continuous probability distributions

such as the uniform, normal, exponential and gamma distribution.

Relations between these continuous probability distributions and the

previously introduced discrete probability distributions are discussed.

• If there is sufficient time at the end of the course, the

concepts of bivariate and multivariate probability distribution included

related concepts such as joint and marginal distribution functions,

conditional probability distribution and independence of stochastic

variables.

### Teaching Methods

Theory lecture 2 times 2 hours per week. Tutorial 1 times 2 hours perweek.

### Method of Assessment

Interbetween exam - individual markFinal exam - individual mark

Individual assignment - individual mark

### Literature

Author: Saeed Ghahramani; Titel: Fundamentals of Probability (withstochastic processes); Third Edition; publication year: 2016;

publisher: CRC Press, Taylor&Francis Group; ISBN: 9781498755016.

### Additional Information

During this course some knowledge gained at the simultaneous courseAnalysis I will be uitilized.