Lecturer(s)
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Ciglerová Hana, PhDr. Ph.D.
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Ayala Aguado Jiří, prof. PhDr. CSc.
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Course content
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1. Introduction and administration, basic overview: Statistics and sociology; basics of statistics and statistical reasoning 2. Software installation: R, RStudio, RMarkDown 3. Analysis using tables and grading 2nd and 3rd degree 4.-5. Basics of multidimensional models - why and when we use them 6.-7. Linear correlation and regression, least squares method 8. Multivariate regression 9. Multivariate regression - special analytical problems 10.-11. Regression diagnostics: unusual and influential data, nonlinearity, heteroscedasticity, collinearity 12.-13. Regression with qualitative dependent variable - binary logistic regression
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Learning activities and teaching methods
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Lecture supplemented with a discussion, Group discussion, Task-based study method, Textual studies, Lecture, Lecture with visual aids, Seminar
- Contact hours
- 52 hours per semester
- Preparation for formative assessments (2-20)
- 20 hours per semester
- Preparation for comprehensive test (10-40)
- 40 hours per semester
- Preparation for an examination (30-60)
- 30 hours per semester
- Individual project (40)
- 40 hours per semester
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prerequisite |
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Knowledge |
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describe and explain basic sociological methods. |
describe the formation of sociological perspectives in the use of sociological methods. |
enumerate and describe basic quantitative methods. |
characterize basic knowledge resulting from empirical quantitative research. |
Skills |
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create formally acceptable professional output. |
use foreign databases of professional journals actively. |
apply and interpret knowledge resulting from the application of quantitative methods. |
use adequate terms corresponding to the terminology of the field in Czech and English. |
Competences |
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N/A |
learning outcomes |
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Knowledge |
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distinguish between quantitative and qualitative variables. |
enumerate the laws of multivariate analysis. |
characterize multivariate analysis using selected sociological data. |
give examples of studies using multivariate analysis. |
Skills |
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obtain appropriate data for multivariate analysis. |
edit data for multivariate analysis. |
apply multivariate analysis to selected data. |
choose the appropriate analytical approach to the selected topic using multivariate analysis. |
defend their analytical approach to specific multivariate data analysis. |
process multivariate data analysis. |
present the results of multivariate data analysis in the form of scientific text. |
Competences |
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N/A |
teaching methods |
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Knowledge |
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Lecture |
Lecture with visual aids |
Lecture supplemented with a discussion |
Seminar |
Task-based study method |
Textual studies |
Group discussion |
Skills |
---|
Lecture |
Lecture with visual aids |
Lecture supplemented with a discussion |
Seminar |
Task-based study method |
Textual studies |
Group discussion |
Competences |
---|
Lecture |
Lecture with visual aids |
Lecture supplemented with a discussion |
Seminar |
Task-based study method |
Textual studies |
Group discussion |
assessment methods |
---|
Knowledge |
---|
Written exam |
Skills demonstration during practicum |
Seminar work |
Continuous assessment |
Project |
Skills |
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Written exam |
Skills demonstration during practicum |
Seminar work |
Continuous assessment |
Project |
Competences |
---|
Written exam |
Skills demonstration during practicum |
Seminar work |
Continuous assessment |
Project |
Recommended literature
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Getting started with stata : for windows. College Station : Stata Press, 2007.
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Stata base reference manual. College Station : Stata Press, 2007. ISBN 1-59718-024-6.
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Stata multivariate statistics : reference manual. College Station : Stata Press, 2007.
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Stata survey data reference : manual. College Station : Stata Press, 2007.
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Allison, Paul D. Multiple Regression: A Primer. Pine Forge Press, 1999.
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Fox, John. Applied regression analysis, linear models, and related methods. Thousand Oaks : SAGE Publications, 1997. ISBN 0-8039-4540-X.
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Fox, John. Nonparametric simple regression: smoothing scatterplots. Thousand Oaks : Sage Publications, 2000. ISBN 0-7619-1585-0.
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Gould, William; Pitblado, Jeffrey; Sribney, William. Maximum likehood estimation with Stata. 3rd ed. College Station : Stata Press, 2005. ISBN 1-59718-012-2.
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Hamilton, Lawrence C. Statistics with STATA : updated for version 9. Belmont : Brooks/Cole, 2006. ISBN 0-495-10972-X.
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Kohler, Ulrich; Kreuter, Frauke. Data analysis using Stata. College Station : Stata Press, 2005. ISBN 1-59718-007-6.
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