Syllabus

Titel
2091 Probability and Statistics (Science Track)
LV-Leiter/innen
Assoz.Prof. PD Dr. Zehra Eksi-Altay, BSc.MSc.
Kontakt
  • LV-Typ
    PI
  • Semesterstunden
    2
  • Unterrichtssprache
    Englisch
Anmeldung
20.11.2019 bis 29.11.2019
Anmeldung über LPIS
Hinweise zur LV
Planpunkt(e) Master
Termine
Wochentag Datum Uhrzeit Raum
Montag 02.12.2019 15:30 - 17:30 D4.0.022
Donnerstag 05.12.2019 15:00 - 17:00 D3.0.225
Montag 09.12.2019 15:30 - 17:30 D4.0.022
Donnerstag 12.12.2019 15:00 - 17:00 TC.3.21
Montag 16.12.2019 15:30 - 17:30 D4.0.022
Donnerstag 19.12.2019 15:00 - 17:00 TC.3.21
Donnerstag 09.01.2020 15:00 - 17:00 TC.5.15
Montag 13.01.2020 15:30 - 17:30 D4.0.022
Donnerstag 16.01.2020 15:00 - 17:00 TC.3.21
Montag 20.01.2020 15:30 - 17:30 D4.0.022
Donnerstag 23.01.2020 15:00 - 17:00 D4.0.022
Montag 27.01.2020 15:30 - 17:30 D4.0.022

Inhalte der LV

This course is a graduate course intended for Economics Masters students. The course aims at building theoretical statistics starting from the basics of probability theory. In particular, the purpose of this course is to give further knowledge in statistics and probability theory which is essential for econometrics and statistical modeling.

Lernergebnisse (Learning Outcomes)

After completing this class successfully the student will have the ability to:

  • define, describe and work with the basic concepts in probability and statistics,
  • use methods and ideas from probability and statistics to solve scientific problems,
  • solve practical problems and interpret the results.


Regelung zur Anwesenheit

Attendance of at least 80% of the classes is necessary to fulfill the requirements.

Lehr-/Lerndesign

The course consists of lectures, accompanying homework assignments and one midterm and the final examinations. The lecture part presents the theoretical concepts. There will be 4 homework assignments related to the subjects covered during the lecture. Students are allowed to hand in the assignments as a group of at most three people.

Leistung(en) für eine Beurteilung

  • 20 % Homework assignments
  • 30 % Midterm Exam
  • 50 % Final Exam


Teilnahmevoraussetzung(en) und Vergabe von Wartelistenplätzen

Familiarity with mathematical concepts such as basic set theory, convergence of sequences and functions, continuity, linear maps and matrices, definite and indefinite integral, differentiation, and Taylor polynomial series is expected. Knowledge in basic probability theory and statistics is desirable.

Literatur

1 Autor/in: [CB] Georg Casella and Roger l. Berger
Titel: Statistical Inference

Verlag: Duxbury Press
Auflage: 2nd
Jahr: 2001
Art: Buch
2 Autor/in: Ramu Ramanathan
Titel: Statistical Methods in Econometrics

Verlag: Academic Press
Anmerkungen: abbreviated RR
Jahr: 1993
3 Autor/in: M. R. Spiegel, J. J. Schiller, R. A. Srinivasan
Titel: Schaum’s Outlines of Probability and Statistics

Verlag: McGraw-Hill
Auflage: 3rd ed. ISBN 978-0-07-154425-2
Anmerkungen: Chapter 1-4
Jahr: 2009
4 Autor/in: J. A. Rice
Titel: Mathematical Statistics and Data Analysis

Verlag: Wadsworth&Brooks/Cole ISBN 0-534-08247-5
Anmerkungen: Chapter 1-5
Jahr: 1988

Erreichbarkeit des/der Vortragenden

zehra.eksi@wu.ac.at

Detailinformationen zu einzelnen Lehrveranstaltungseinheiten

Einheit Datum Inhalte
1

Basics of probability, conditional probability and independence, random variables, distribution functions.

Reference: CB chapter 1, 2.


2

Transformations of random variables, expected values, moments and moment generating functions.

Reference: CB chapter 2,3.


3

Discrete distributions, continuous distributions.

Reference: CB chapter 3.


4

Multivariate distributions, joint and marginal distributions. 

Reference: CB chapter 4.


5

Multivariate normal, Chi-square distribution, multinomial distribution, probability inequalities.

Reference: CB chapter 4.

6

Midterm Exam


7

Sampling theory, random samples, sampling distributions, convergence concepts, law of large numbers, central limit theorem.

Reference: CB chapter 5


8

Estimation: Methods of finding estimators; maximum likelihood estimators, method of moments, Bayes estimators.

Reference: CB chapter 7.

9

Estimation: Methods of evaluating estimators; mean squared error, best unbiased estimators, sufficiency and unbiasedness.

Reference: CB chapter 7.

10

Basic concepts of hypothesis testing, methods of finding tests (Likelihood ratio test, etc.)

Reference: CB Chapter 8 

11

Hypothesis testing; methods of evaluating tests.

Reference: CB chapter 8.


12 Final Exam
Zuletzt bearbeitet: 20.03.2019



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