Január - 2019
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Subject data sheet

Quantitative research methods

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Code: 4KO03NBK80M
Name: Quantitative research methods
Number of hours per semester: 2+2
Credits: 6
Fall/Spring: Spring
Language: English
Prerequisites: none
Course type: mandatory
Department: Közgazdálkodás és Közpolitika Tanszék
A Course leader: Hajnal György

Course description: The plan and ambition of the course:
Main objectives: (i) familiarize students with core concepts and instruments of empirical research; (ii) develop skills enabling students to apply them in real-life settings; (iii) help them prepare for the thesis research.
Examples are usually drown from public administration / policy setting. BUT: the course develops generic skills indispensable in corporate etc. settings too!

Week Topic

1 "Components, goals and structure of the course.
Introduction to survey methods. Methods of data collection. Self-completion and interviewer-administered surveys. Personal and telephone interviews. CAPI, CATI and CASI methods. Online survey tools."
2 Guidelines for designing questionnaires. Defining the information required to answer a research question. Screening and exclusion questions. Types of question.
3 Rating scales. Balanced vs. unbalanced rating scales. Attitude measurement. Visual aids in questionnaires.
4 Socio-demographic and sensitive questions. Writing the questionnaire. Language and style.
5 An overview of SPSS. Structure of data file. Creating and editing data file. Variable types. Inputing and importing data. (CH01-03).
6 Presentation and discussion of the Questionnaires
7 Managing data: recode, calculate, select, sort (Ch04). Single variable statistics. Descriptive statistics. (Ch06-07)
8 Relationship between two variables I.: nominal-nominal. (Crosstab; Row vs. Col%)
9 Relationship between two variables I II.: nominal vs. scale (paired-sample t-test, 1-way ANOVA – Ch1/11, 12). Relationship between two variables I III.: scale vs. scale (bivariate corr.)
10 2-way ANOVA (Ch13)
11 Simple and multiple linear regressions (Ch15, 16)

Assessment, grading: Component #1: Questionnaire development (group work; 40 points)
Component #2: Written mini-tests (elements of the given class; 20 points)
Component #3: End-of-semester written exam (computer lab, 40 points)

Aims and objectives and description of the course: 

Time of class: 

Learning outcomes: 


Compulsory readings:

  • Darren George – Paul Mallery: SPSS for Windows Step by Step, 8th Edition, Pearson, 2008

Recommended readings:

Compulsory readings:
Recommended readings:


Dr. Rencz Fanni, Dr. Brodszky Valentin Péter

Last modification: 2018-12-11 20:37:19


Course codeTypeSemesterInstructors
GGyakorlat2018/19/2Dr. Rencz Fanni, Dr. Brodszky Valentin Péter

A "Tantárgyfelelős tanszék", a tantárgyfelelős neve a tantárgy oktatói és a kurzusinformációk automatikusan frissülnek a tanulmányi rendszerünk alapján.