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The analysis of social data

General data

Course ID: 2102-L-D4ANDS-SPEC
Erasmus code / ISCED: 14.1 Kod klasyfikacyjny przedmiotu składa się z trzech do pięciu cyfr, przy czym trzy pierwsze oznaczają klasyfikację dziedziny wg. Listy kodów dziedzin obowiązującej w programie Socrates/Erasmus, czwarta (dotąd na ogół 0) – ewentualne uszczegółowienie informacji o dyscyplinie, piąta – stopień zaawansowania przedmiotu ustalony na podstawie roku studiów, dla którego przedmiot jest przeznaczony. / (0312) Political sciences and civics The ISCED (International Standard Classification of Education) code has been designed by UNESCO.
Course title: The analysis of social data
Name in Polish: Analiza danych społecznych
Organizational unit: Faculty of Political Science and International Studies
Course groups: (in Polish) Nauki Polityczne - DZIENNE I STOPNIA 4 semestr 2 rok - przedmioty wszystkie
ECTS credit allocation (and other scores): 3.00 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: Polish
Prerequisites (description):

(in Polish)


Short description:

After completing the course the student will gain systematic knowledge in the field of analysis of quantitative and qualitative data in the context of the political, social and economic processes.
Full description:

Course is provide participants with the knowledge base the analysis of current data of social and political science, as well as the state of research and analysis of socio-political changes in Poland and in the world. Student equipped with such knowledge will be freely used the elementary concepts of quantitative and qualitative data analysis and applying basic methods and analytical tools. In addition, it will be able to analyze a social and political processes and their mutual relations by means of quantitative and qualitative data analysis. After completion of the course students should know and be able to take advantage of Polish and European sources of statistical data (surveys, public statistics). During the course, the student acquires the ability to acquire, prepare and interpret data sets for analysis calculations in the PSPP / SPSS for basic measures for the description and diagnosis of social and political phenomena, as well as the use of methods to study the relationships of dependency and prediction (forecasting) of the statistical. Student will be able to interpret the results of calculations prepared in the PSPP / SPSS, isolated prepare data set for analysis, carried out on the basis of calculations in the PSPP / SPSS, primarily in the basics of descriptive statistics and methods based on statistical inference. In addition, after completing the course, students will be adequately interpreted the results of calculations prepared in the PSPP / SPSS and created simple reports and presentations according to the accepted rules. Students will acquire the ability to carry out elementary qualitative data analysis method to analyze the content using programs: Weft QDA / Open Code.
Bibliography:

1/ C. Seale, Wykorzystanie komputera w analizie danych jakościowych, [w:] Prowadzenie badań jakościowych, D. Silverman (red.), Wydawnictwo Naukowe PWN, Warszawa 2008, s. 233-256.

2/ D. Mider, A. Marcinkowska, Analiza danych ilościowych dla politologów. Praktyczne wprowadzenie z wykorzystaniem programu GNU PSPP, ACAD, Warszawa 2013, Rozdział 1. Geneza i rozwój analizy danych ilościowych, s. 31-46, Rozdział 15. Wprowadzenie do wnioskowania statystycznego, (podrozdział 15.1.3, 15.1.3.1), s. 257-262.

3/ D. Mider, A. Marcinkowska, Analiza danych ilościowych dla politologów. Praktyczne wprowadzenie z wykorzystaniem programu GNU PSPP, ACAD, Warszawa 2013, Rozdział 4. Techniczne podstawy pracy z PSPP, Rozdział 5. Struktura i organizacja zbioru danych w PSPP, s. 63-98.

4/ D. Mider, A. Marcinkowska, Analiza danych ilościowych dla politologów. Praktyczne wprowadzenie z wykorzystaniem programu GNU PSPP, ACAD, Warszawa 2013, Rozdział 7. Rekonfiguracja zbioru danych, s. 109-128.

5/ D. Mider, A. Marcinkowska, Analiza danych ilościowych dla politologów. Praktyczne wprowadzenie z wykorzystaniem programu GNU PSPP, ACAD, Warszawa 2013, Rozdział 8. Przekształcenia zmiennych w zbiorze danych (podrozdziały 8.1.-8.5.), s. 129-143.

6/ D. Mider, A. Marcinkowska, Analiza danych ilościowych dla politologów. Praktyczne wprowadzenie z wykorzystaniem programu GNU PSPP, ACAD, Warszawa 2013, Rozdział 8. Przekształcenia zmiennych w zbiorze danych (podrozdziały 8.5.1, 8.6., 8.7., 8.8.), s. 143-152.

7/ D. Mider, A. Marcinkowska, Analiza danych ilościowych dla politologów. Praktyczne wprowadzenie z wykorzystaniem programu GNU PSPP, ACAD, Warszawa 2013, Rozdział 9. Analiza częstości występowania zjawisk, Rozdział 10. Miary tendencji centralnej (pozycyjne), Rozdział 11. Miary rozrzutu (dyspersji) – podrozdziały 11.2.-11.4., s. 155-166, 167-182, 183-186.

8/ D. Mider, A. Marcinkowska, Analiza danych ilościowych dla politologów. Praktyczne wprowadzenie z wykorzystaniem programu GNU PSPP, ACAD, Warszawa 2013, Rozdział 14. Regresja liniowa - elementarna metoda predykcji statystycznej, s. 233-250.

9/ D. Mider, A. Marcinkowska, Analiza danych ilościowych dla politologów. Praktyczne wprowadzenie z wykorzystaniem programu GNU PSPP, ACAD, Warszawa 2013, Rozdział 13. Badanie zależności między zmiennymi – podrozdziały 13.1.1., 13.1.2., 13.2.2.1., s. 201-209, 213-215.

10/ G. Gibbs, Analizowanie danych jakościowych, Wydawnictwo Naukowe PWN, Warszawa 2011, Rozdział 4. Kodowanie tematyczne i kategoryzacja, s. 79-106.

11/ M.B. Miles, A.M. Huberman, Analiza danych jakościowych, Wydawnictwo „Transhumana”, Białystok 2000, podpunkty: D. Odmiany badań jakościowych, E. Natura badań jakościowych, s. 5-11.
Learning outcomes:

KNOWLEDGE

EK1. He knows the directions of research of political science and their relationships with research in other social sciences (W09).

SKILLS

EK4. Student is able to use theoretical knowledge in the field of political science and related disciplines to analyze and interpret phenomena and processes in the area of ​​policy (U03).

EK5. Can use basic theories and the use of methods and techniques for the diagnosis and prognosis of various phenomena in the policy area (U05).

EK7. Can develop their professional skills, using different sources (in the native language and a foreign language) as well as modern technology (ICT) (U08).

EK8. Student has the ability to present their own ideas, justify them, and to confront the views of other students and various authors (U09).

EK10. Student has the ability to collect, hierarchies, information processing and creation of typical works written in Polish and foreign language on specific issues with the use of the basic theoretical concepts and different sources (U11).

COMPETENCES

EK15. Has need to further supplement the knowledge and improve and expand skills (K07).
Assessment methods and assessment criteria:

Students may, during the course receive a maximum of 35 points. In the course of making the required standard activity (independent exercise of PSPP / SPSS. Weft QDA / Open Code, activities, attendance, presentation made independently analyzes).
Practical placement:

None

Classes in period "Summer semester 2023/24" (in progress)

Time span: 2024-02-19 - 2024-06-16
Selected timetable range:
Navigate to timetable
Type of class:
Seminar, 30 hours more information
Coordinators: Daniel Mider
Group instructors: Daniel Mider
Students list: (inaccessible to you)
Examination: Course - Grading
Seminar - Grading
Short description:

Social data analysis (30 hours) - analysis of quantitative and qualitative data in the context of political, social and economic processes.
Full description:

The basic aim of the course is to provide the participants with the basic knowledge of analysing current social and political data, as well as the state of conducting socio-political research and analysis in Poland and abroad. The student equipped with such knowledge will be able to freely use elementary concepts used in quantitative and qualitative data analysis and the application of basic methods and analytical tools. In addition, they will be able to analyse social and political processes, their interrelationships using quantitative and qualitative data analysis. Upon completion of the course, students should know and be able to use Polish and European sources of statistical data (survey research, public statistics). During the course, the student will acquire the ability to obtain, prepare and interpret data sets for analysis, carry out calculations in the PSPP/SPSS programme in the scope of basic measures for the description and diagnosis of social and political phenomena, as well as apply methods to study relationships, dependencies and statistical prediction (forecasting). Students will be able to interpret the results of calculations prepared in PSPP/SPSS, independently prepare a dataset for analysis, carry out calculations on its basis in PSPP/SPSS, primarily in the field of basics of descriptive statistics and methods based on statistical inference. In addition, students will adequately interpret the results of calculations prepared in PSPP/SPSS and create simple reports and presentations according to accepted technical and aesthetic principles. Students will acquire the ability to carry out elementary qualitative data analysis by content analysis using the programs: Weft QDA/Open Code.
Bibliography:

1/ C. Seale, Using the computer in qualitative data analysis, [in:] Conducting qualitative research, D. Silverman (ed.), PWN Scientific Publishers, Warsaw 2008, pp. 233-256.

2/ D. Mider, A. Marcinkowska, Quantitative data analysis for political scientists. A practical introduction using the GNU PSPP program, ACAD, Warsaw 2013, Chapter 1 Genesis and development of quantitative data analysis, pp. 31-46, Chapter 15 Introduction to statistical inference, (subsection 15.1.3, 15.1.3.1), pp. 257-262.

3/ D. Mider, A. Marcinkowska, Quantitative data analysis for political scientists. A practical introduction using the GNU PSPP programme, ACAD, Warsaw 2013, Chapter 4 Technical basis for working with PSPP, Chapter 5 Structure and organisation of the data set in PSPP, pp. 63-98.

4/ D. Mider, A. Marcinkowska, Quantitative data analysis for political scientists. A practical introduction using GNU PSPP, ACAD, Warsaw 2013, Chapter 7. Reconfiguration of the dataset, pp. 109-128.

5/ D. Mider, A. Marcinkowska, Quantitative data analysis for political scientists. A practical introduction using the GNU PSPP program, ACAD, Warsaw 2013, Chapter 8. Transformations of variables in a dataset (subsections 8.1.-8.5.), pp. 129-143.

6/ D. Mider, A. Marcinkowska, Quantitative data analysis for political scientists. A practical introduction using the GNU PSPP program, ACAD, Warsaw 2013, Chapter 8. Transformations of variables in a data set (subsections 8.5.1, 8.6., 8.7., 8.8.), pp. 143-152.

7/ D. Mider, A. Marcinkowska, Quantitative data analysis for political scientists. Practical introduction with the use of GNU PSPP program, ACAD, Warsaw 2013, Chapter 9. Frequency analysis of phenomena, Chapter 10. Measures of central tendency (positional), Chapter 11. Measures of scatter (dispersion) - subsections 11.2.-11.4., pp. 155-166, 167-182, 183-186.

8/ D. Mider, A. Marcinkowska, Quantitative data analysis for political scientists. Practical introduction with the use of GNU PSPP program, ACAD, Warsaw 2013, Chapter 14 Linear regression - elementary statistical prediction method, pp. 233-250.

9/ D. Mider, A. Marcinkowska, Quantitative data analysis for political scientists. Practical introduction with the use of GNU PSPP program, ACAD, Warsaw 2013, Chapter 13. Investigating dependencies between variables - subsections 13.1.1., 13.1.2., 13.2.2.1., pp. 201-209, 213-215.

10/ G. Gibbs, Analysing qualitative data, PWN Scientific Publishers, Warsaw 2011, Chapter 4 Thematic coding and categorisation, pp. 79-106.

11/ M.B. Miles, A.M. Huberman, Qualitative data analysis, Transhumana Publishing House, Bialystok 2000, subp: D. Varieties of qualitative research, E. The nature of qualitative research, pp. 5-11.

Translated with www.DeepL.com/Translator (free version)
Notes:

None.

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