Sylabus
* Structure of Lessons:
1. Introduction to Quantitative Data Analysis.
2. Basics of quantitative research - mass data, selection of units, measuring, hypotheses, secondary analysis.
3. Validity and reliability, creation of on-line questionnaire.
4. Introduction to SPSS, basic functions.
5. Basic rules to forming questionnaires, types of questions, their coding in SPSS.
6. Working with mass data before analysis.
7. Basics of one-dimensional analysis.
8. Normal distribution.
9. Standardized normal distribution.
10. Statistical inference a testing of hypotheses.
11. Transformation of variables I (recode).
12. Transformation of variables II.
13. Conclusion. * 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.
Anotace
The course covers the basic analysis of quantitative data from social surveys. Topics include basic knowledge about of quantitative research, simple descriptive statistics (central tendency and dispersion, frequency distributions), and elementary data manipulation; other topics are normal distribution and, transformation of variables. The Ffocus is on conceptual understanding and practical knowledge. Students will gain experience practicing their learning through various assignments using the statistical software SPSS. Students will learn how to (a) create datasets (e.g. from their own survey) and assess the type and quality of data and potential problems
(missing values, polarized responses, outliers, etc.) and transform variables (recoding); (b) use basic descriptive and explorative statistical methods to answer a simple research question, assess the validity of simple hypotheses and graphically present the results; (cd) control the basic functions in the statistical software SPSS, e.g. elementary data transformation, descriptive statistics, and simple graphs. Final credit will be fulfilled with own simple data analysis.