Universität Wien
Achtung! Das Lehrangebot ist noch nicht vollständig und wird bis Semesterbeginn laufend ergänzt.

240090 UE MM1 - Methoden der quantitativen Entwicklungsforschung (2022S)

5.00 ECTS (2.00 SWS), SPL 24 - Kultur- und Sozialanthropologie
Prüfungsimmanente Lehrveranstaltung
Moodle

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 30 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

Depending on the evolution of the pandemic and the corresponding regulation by the University of Vienna, the course will take place in the following formats (ranked by preference, and subject to feasibility): (1) physical presence, (2) hybrid format, (3) online.

  • Montag 07.03. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
  • Montag 14.03. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
  • Montag 21.03. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
  • Montag 28.03. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
  • Montag 04.04. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
  • Montag 25.04. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
  • Montag 02.05. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
  • Montag 09.05. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
  • Montag 16.05. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
  • Montag 23.05. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
  • Montag 30.05. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
  • Montag 13.06. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
  • Montag 20.06. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01
  • Montag 27.06. 09:45 - 11:15 Seminarraum 7, Kolingasse 14-16, OG01

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

This is an introduction to applied statistics. The main goal of the course is for students to develop the necessary foundations and skills to implement quantitative empirical research independently. Students are required to make "hands-on" applications of the material studied in the course.

Art der Leistungskontrolle und erlaubte Hilfsmittel

Students will be marked according to 3 different homeworks (20% each) and a final project (40%). Failure to hand in any of these implies a negative evaluation of the course.

Mindestanforderungen und Beurteilungsmaßstab

Students should prove a good command (at least 50%) of the course’s topics. 50% - 60% implies a 4; 60% - 70% a 3; 70% - 85% a 2; above 80% a 1.

Prüfungsstoff

The course’s main topics are descriptive statistics, probability, random variables, inference, regression analysis.

Literatur

The course has been prepared with two textbooks:

Newbold, Carlson and Thorne (2013): Statistics for Business and Economics, Pearson, 8th edition, (NCT)

Shafer and Zhang (2012): Beginning Statistics (legally available online for free), (SZ)

Other introductory statistics textbooks are likely to provide very similar treatments.

Many examples have been borrowed from the following (rather entertaining) books:

1. Charles Wheelan (2013): Naked Statistics. Stripping the Dread from the Data, W.W. Norton.

2. Leonard Mlodinow (2008): The Drunkard'S Walk. How Randomess Rules Our Lives, Pantheon Books.

3. Nate Silver (2012): The Signal and the Noise. Why So Many Predictions Fail, But Some Don't, Penguin Books. 
I. Introduction

William Easterly (2009): "The Anarchy of Success," The New York Review of Books, 56(15), October.
SZ: Chapter 1

II. Descriptive statistics

NCT: Chapters 1 and 2.
SZ: Chapter 2

III. Probability

NCT: Chapter 3.
SZ: Chapter 3

IV. Random variables

NCT: Chapters 4-6.
SZ: Chapters 4-6

V. Inference

NCT: Chapters 7-10.
SZ: Chapters 7-9

VI. Regression Analysis

NCT: Chapters 11-13.
SZ: Chapter 10

Miguel Niño-Zarazúa (2012): “Quantitative Analysis in Social Sciences: A Brief Introduction for Non-Economists,” manuscript, WIDER.

Zuordnung im Vorlesungsverzeichnis

MM1

Letzte Änderung: Mi 09.02.2022 10:48