Poslední úprava: PhDr. Blanka Jirkovská, Ph.D. (25.09.2020)
This course follows Quantitative Data Analysis I. The course covers the basic analysis of quantitative data from
social surveys. Topics include simple descriptive statistics (central tendency and dispersion, frequency
distributions, cross-tabulation, association/correlation), and elementary data manipulation; other topics are the
logic of elaboration, data standardization, introduction to inferential statistics, basic principles of inferential
statistics, i.e. statistical testing of hypotheses and multivariate analysis. Focus is on conceptual understanding and
practical knowledge. Students will gain experience practicing their learning through various assignments using the
statistical software SPSS. The fFinal exam will be fulfilled with own data analysis and a test (analysis of
contingency tables).
Distance education will be provided through the provision of learning materials, consultations in MS Teams and practical training of examples in SPSS.
Poslední úprava: PhDr. Blanka Jirkovská, Ph.D. (25.09.2020)
A follow-up to the course ‘Quantitative Data Analysis’, the aim of which is to extend students' knowledge and practical skills required for quantitative data management, exploratory and descriptive analysis, and statistical methods.
Distance education will be provided through the provision of learning materials, consultations in MS Teams and practical training of examples in SPSS.
Požadavky ke zkoušce - angličtina
Poslední úprava: PhDr. Blanka Jirkovská, Ph.D. (13.06.2019)
seminar paper - presentation of primary or secondary quantitative data analysis, mostly analysis of the second degree - introducing aims, research questions, methodology, main results, interpretation
test - quantitative data analysis of the second degree, working with IBM SPSS Statistics
Sylabus
Poslední úprava: Mgr. Karolína Šedivcová (04.06.2019)
Structure of Lessons:
1. Repetition of basic environment of SPSS.
2. Summary of basic analysis of first order.
3. Comparison of means, T-test, ANOVA.
4. Basics of second order analysis in categorical variables - chi-square.
5. Working with Crosstabs.
6. Deeper analysis of Crosstabs.
7. Rules of sociological interpretation in categorical variables.
8. Correlation.
9. Elaboration.
10. Simple linear regression.
11. Multiple linear regression.
12. Factor analysis.
Required reading:
BRYMAN, A. Social research methods. Oxford: Oxford University Press, 2008. ISBN 0199202958.
Recommended reading:
BABBIE, E. Elementary analyses. In The Practice of social Research. 7th Edition. Belmont: Wadsworth, 1995. Pp. 375-394. ISBN 0-534-18744-7.
De VAUS, D. A. Surveys in social research. Fifth edition. London: Routledge. 2002.
(chapters 10, 12 to 16)
GARSON, G. D. Quantitative Research in Public Administration (PA 765 - 766).
IBM SPSS Statistics 20 Brief Guide. [online]. IBM Corporation 1989, 2011. Available at: ftp://public.dhe.ibm.com/software/analytics/spss/documentation/statistics/20.0/en/client/Manuals/IBM_SPSS_Statistics_Brief_Guide.pdf
IBM SPSS Statistics Base 20. [online]. IBM Corporation 1989, 2011. Available at: ftp://public.dhe.ibm.com/software/analytics/spss/documentation/statistics/20.0/en/client/Manuals/IBM_SPSS_Statistics_Base.pdf. (chapters 2, 3, 4, 5, 6, 7)
MILLER, J. E. The Chicago guide to writing about numbers. Chicago: University of Chicago Press, 2004. (selected chapters)
STATSOFT, Inc. Electronic Statistics Textbook. Tulsa, OK: StatSoft, 2010.
TREIMAN, D. J. Quantitative data analysis: doing social research to test ideas. San Francisco: Jossey-Bass, 2009. ISBN 780470380031.
Vstupní požadavky - angličtina
Poslední úprava: Mgr. Karolína Šedivcová (19.06.2019)
The course follows the topics discussed at YHM515 - Quantitative Data Analysis I. Nevertheless, it is opened also for students of other departments or Erasmus students, but it requires the previous knowledge of statistic work in SPSS.
