Universität Wien
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240090 UE MM1 - Methods of Quantitative Research in Development Studies (2022S)

5.00 ECTS (2.00 SWS), SPL 24 - Kultur- und Sozialanthropologie
Continuous assessment of course work
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 30 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

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.

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

Information

Aims, contents and method of the course

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.

Assessment and permitted materials

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.

Minimum requirements and assessment criteria

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.

Examination topics

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

Reading list

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.

Association in the course directory

MM1

Last modified: We 09.02.2022 10:48