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## Statistics

2019-2020

### Course Objective

The course statistics is an introduction into the basic concepts of
mathematical statistics. At the end of the course the student can
formulate statistical models, derive different types of estimators,
formulate and execute various hypothesis tests and construct confidence
intervals.

### Course Content

In statistics one tries to make statements about the generating process
behind observed data. The lectures include: statistical models, point
estimations, hypothesis tests, and the construction of confidence
intervals; probability theory and classes of probability distributions
are added to these topics when they are needed. The material is
illustrated on the basis of many (practical) examples. In this course,
the emphasis is on parametric statistics, in which the probability
distribution is known up to a finite number of parameters.

### Teaching Methods

Lectures: 2 times 2 hours of lectures per week
Tutorials: 1 time 2 hours of tutorial per week

The purpose of the lectures is to gain new knowledge and insights from
mathematics. As the course progresses so will the level of abstractness.
It is very helpful to prepare yourself by reading relevant sections in
the book and/or lecture notes before you come to the lecture.

In the tutorials we focus on solving statistical problems in the form of
exercises. Most exercises are of an applied nature although some will
ask you to provide a theoretical result. Answers are important, but the
route to the answer is obviously more important than the answer itself.
Note that the exam questions will be very similar to the tutorial
exercises. The tutorials are therefore a useful preparation for the
examination.

### Method of Assessment

Individual assignment
Midterm - individual assessment
Final written exam - individual assessment

### Literature

"Statistical Inference" by G. Casella and R.L. Berger (2008),
International Edition of the 2nd revised edition, Cengage Learning.

Lecture notes.

### Target Audience

First year Bsc Econometrie & Operations Research and first year Bsc
Econometrics and Data Science.

### Recommended background knowledge

This course presumes that students are familiar with:
- Abstract reasoning
- Calculus
- Probability theory

### General Information

Course Code E_EOR1_STAT 6 EC P4+5 100 English School of Business and Economics mr. M.H.C. Nientker mr. M.H.C. Nientker

### Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Seminar, Lecture
Target audiences

This course is also available as: