Course ObjectiveThe 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 ContentStatistics 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
Teaching MethodsLectures, exercise classes
Method of AssessmentTwo written exams - midterm and final - each contributing 50% to the
final grade. In the resit, both exams can be retaken or only one of
Literature"An introduction to mathematical statistics" by Fetsje Bijma, Marianne
Jonker and Aad van der Vaart.
Target AudienceBSc Business Analytics and BSc Mathematics, Year 2
Recommended background knowledgeCalculus / Single variable calculus and Probability theory.
|Language of Tuition||English|
|Faculty||Faculty of Science|
|Course Coordinator||M. Frolkova|
You need to register for this course yourself
Last-minute registration is available for this course.
|Teaching Methods||Seminar, Lecture|
This course is also available as: