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## Statistics

2018-2019

### Course Objective

The course Statistics is a first introduction to the basic concepts of
mathematical statistics. After completing this course the student can
set up a basic statistical model and

1. Parameter estimation: the student can construct different types of
point estimators for the unknown model parameters: ML, MM, Bayesian.
They can compare different estimators in the MSE sense.

2. Hypothesis testing: the student can test claims about population
proportions and the parameters of normal data in a 1-sample and
2-samples settings. They can pick the sample size to guarantee a good
power of the test. They can test in multiple ways: with critical
regions, p-values and confidence intervals.

3. Confidence intervals: the student can construct interval estimations
for the unknown model paramerters: via pivots (ad-hoc approach) and by
two universally working methods (ML and MR).

4. Optimality theory: the student can construct estimators that are the
best in the MSE sense. They can construct the best (most powerful) test
for simple hypotheses.

### Course Content

Statistics is the field of inferring conclusions about underlying
distributions of observed data. In this course we deal with the topics:
statistical model, estimation, hypothesis testing, and optimality.

In this course, we limit ourselves to parametric statistical models,
which means that underlying distributions are known up to some unknown
parameter(s).

### Teaching Methods

Lectures, exercise classes

### Method of Assessment

Two written exams - midterm and final - each contributing 50% to the
final grade. In the resit, both exams can be retaken or only one of
them.

### Literature

"An introduction to mathematical statistics" by Fetsje Bijma, Marianne
Jonker and Aad van der Vaart.

### Target Audience

BSc Business Analytics and BSc Mathematics, Year 2

### Recommended background knowledge

Calculus / Single variable calculus and Probability theory.

### General Information

Course Code X_400004 6 EC P1+2 200 English Faculty of Science M. Frolkova M. Frolkova M. Frolkova

### 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: