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Quantitative Research Methodology for Social Sciences

General data

Course ID: 2400-SZD-QPE-QRM
Erasmus code / ISCED: (unknown) / (unknown)
Course title: Quantitative Research Methodology for Social Sciences
Name in Polish: Quantitative Research Methodology for Social Sciences
Organizational unit: Faculty of Economic Sciences
Course groups: (in Polish) Przedmioty WNE dla programu QPE w Międzydziedzinowej Szkole Doktorskiej (ZIP)
ECTS credit allocation (and other scores): (not available) Basic information on ECTS credits allocation principles:
  • the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS;
  • the student’s weekly hourly workload is 45 h;
  • 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes;
  • weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS;
  • work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load.
Language: English
Type of course:

obligatory courses

Mode:

Classroom

Short description:

The course focuses on the organization and systematization of knowledge in the field of social sciences methodology. It assumes that students during the first and second degree studies encountered basics of methodology and statistics, and also implemented their own research projects in practice. The first part is an introduction to the philosophical and epistemological basis of scientific research in social sciences. Then, the scientific research process is presented. Emphasis is placed on the measurement methods - the theory of questionnaires and tests, psychophysiological methods and the analysis of Internet data. As a summary, ethics of scientific research is presented, taking into account the importance of reliable data analysis and responsibility for scientific publication

Full description:

1. Introduction to science: What is scientific truth?

a. Induction and deduction

b. Empirical and logical evidence

c. Science goals: Description, Explanation, Prediction

2. Determinism and probability

a. Basic statistical terms.

b. Research as explaining the variance

c. Karl Popper and Parmenides actually

3. The logic of research process

a. From problem statement to conclusions

4. Problem statement

a. The variables space: dependent and independent variables

b. Mediators and moderators

c. Correlation and causative explanations

5. Hypotheses

a. Assumptions vs hypotheses

b. Elements of statistical inference theory

c. One-tail and Two-tail hypotheses

d. Conditions of proper hypotheses

6. Operationalization

a. Measurement and manipulation

7. Research planning

a. Effect size and test power

b. Sample representativeness

c. Analyses and conclusions

8. Measurement theory

a. Empirical and mathematical systems

b. Existence and uniqueness of measurement functions

c. Relationships between objects and their reproduction in mathematical systems

d. Measurement scales- nominal, ordinal and interval.

9. Classic psychometry

a. Reliability and error of measurement

b. Norming and standardization

c. Validity of measurement and validity of research plans

10. Item response theory

a. Basic principles

b. Examples

11. Psychophysiological methods in social research

a. Eyetracking

b. HR and HRV

c. GSR

12. Experimental schemas

a. Classic experimental setup

b. Reduced (without pretest or control group)

c. Latin Square

13. Errors in experiment planning

a. Internal validity of experimental setup

b. External validity

14. Introduction to big data analysis

a. Success stories and possibilities of non-responsive data analysis

b. Artifacts and how to avoid them

15. Ethics and Questionable research practices

a. Research on human subjects

b. QRP in data analyzing

c. Scientific publishing

Bibliography:

- Weinberg, S. (2003) Scientists: Four gold lessons. Nature 426, 389

- Gravetter, FJ., Forzano L-A. B. (2012) Research Methods for the Behavioral Sciences

4 th edition. Wadsworth, Cengage Learning

- Lord, F. M. (1953). On the Statistical Treatment of Football Numbers.

Learning outcomes:

Student:

1. Develops advanced reflection on empirical social research (P8S_WG)

2. Adequately uses various methods of quantitative data acquiring (P8S_UW)

3. Analyses critically publications and research reports (P8S_KK)

4. Recognizes own responsibility for research and publication of own projects. (P8S_KR)

Assessment methods and assessment criteria:

Multiple choice test (60%)

Empirical paper review (40%)

Student must obtain at least 60% points.

This course is not currently offered.
Course descriptions are protected by copyright.
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