Statistics

2019-2020

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
Credits 6 EC
Period P1+2
Course Level 200
Language of Tuition English
Faculty Faculty of Science
Course Coordinator prof. dr. M.C.M. de Gunst
Examiner prof. dr. M.C.M. de Gunst
Teaching Staff prof. dr. J.H. van Zanten

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: