Lecture: Statistics 2

Winter term 2024/2025

For organizational questions, please contact Ricardo Blum.
Links: MUESLI; Moodle; heiCO.
The course will be made available in Moodle on October 14. The registration key will be send via MUESLI.

Description

This is a master level course in Mathematical Statistics. Topics include:
  • Introduction
  • Extremum estimators
  • Consistency of extremum estimators
  • Asymptotic normality of extremum estimators
  • Testing procedures based on extremum estimators
  • ML-estimators, differentiability in quadratic mean
  • Nonparametric regression
  • Local Asymptotic Normality (LAN)
  • Contiguity, binary experiments
  • Optimality theory in LAN experiments
  • Semiparametric models

Place and Date

  • Lecture: Wednesdays and Fridays 11:15 - 12:45, Place: SR 5 (Mathematikon, INF 205)
    The first lecture takes place on Wednesday, October 16.
  • Exercise classes: Tuesdays 14:15 - 15:45, Place: SR 5 (Mathematikon, INF 205)
    The first exercise class takes place on Tuesday, October 22.
    Hand-in of exercise sheets: on Fridays, 13:15. Please hand in your solutions in box no. 09 in the 1st floor of the Mathematikon.
  • Exam: TBA. There will be a registration for the exam. Information follow via e-mail.

Registration in MUESLI and heiCO

If you are interested in taking the course, please register in MUESLI. Additionally, you need to register in heiCO.

Moodle

We will use Moodle, where materials to the lecture will be published. The password for registration to the moodle course will be sent via MUESLI at the beginning of the semester.

Assignments

The lecture is accompanied by weekly assignments which need to be handed in. In order to take the exam it is required to achieve at least 50% in the assigments. Solutions to the assignments will be discussed in the exercise classes.

Final exam and admission

Admission to the final exam gets who either

  • achieved at least 50% of the points on the assignment sheets
or

  • was accepted for examination at an earlier course "Statistics 2" and has not yet lost the examination claim.
The final grade is fully determined by the exam.

Module description

  • Lecture with exercises (4+2 SWS), 8 ECTS
  • This lecture is part of "Grundmodul Statistik und Wahrscheinlichkeitsrechnung", see Modulhandbuch Master Mathematik (MM16).
  • Recommended: Probability Theory 1, Statistics 1.