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Main menu for Browse IS/STAG
Course info
KSS / KVASA
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Course description
Department/Unit / Abbreviation
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KSS
/
KVASA
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Academic Year
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2014/2015
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Academic Year
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2014/2015
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Title
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Applications for Quantitative Data
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Form of course completion
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Exam
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Form of course completion
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Exam
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Accredited / Credits
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Yes,
8
Cred.
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Type of completion
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Combined
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Type of completion
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Combined
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Time requirements
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Lecture
2
[Hours/Week]
Seminar
2
[Hours/Week]
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Course credit prior to examination
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Yes
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Course credit prior to examination
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Yes
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Automatic acceptance of credit before examination
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Yes in the case of a previous evaluation 4 nebo nic.
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Included in study average
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YES
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Language of instruction
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English
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Occ/max
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Automatic acceptance of credit before examination
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Yes in the case of a previous evaluation 4 nebo nic.
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Summer semester
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0 / -
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0 / -
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0 / -
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Included in study average
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YES
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Winter semester
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0 / -
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0 / -
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0 / -
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Repeated registration
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NO
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Repeated registration
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NO
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Timetable
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Yes
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Semester taught
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Winter + Summer
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Semester taught
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Winter + Summer
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Minimum (B + C) students
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10
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Optional course |
Yes
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Optional course
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Yes
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Language of instruction
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English
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Internship duration
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0
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No. of hours of on-premise lessons |
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Evaluation scale |
1|2|3|4 |
Periodicity |
každý rok
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Evaluation scale for credit before examination |
S|N |
Periodicita upřesnění |
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Fundamental theoretical course |
No
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Fundamental course |
No
|
Fundamental theoretical course |
No
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Evaluation scale |
1|2|3|4 |
Evaluation scale for credit before examination |
S|N |
Substituted course
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None
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Preclusive courses
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KSS/KVAS
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Prerequisite courses
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N/A
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Informally recommended courses
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N/A
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Courses depending on this Course
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N/A
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Histogram of students' grades over the years:
Graphic PNG
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XLS
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Course objectives:
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The class teaches students how to use STATA- a general multipurpose package for the analysis of quantitative data. The class covers both data management and data analytic skills. It complements the introductory statistics class by teaching students how to compute basic statistics in a computer environment
In this practically oriented course students learn how to analyse quantitative data while they also become familiar with particular phases of a research, so they would be prepared for an independent empirical work. During the semester students have to manage work with a statistical software - from creating the data matrix and saving it to making the univariant and bivariant analysis. The course prepares students for writing an emipirical Bachelor or Master dissertation.
In this practically oriented course students learn how to analyse quantitative data while they also become familiar with particular phases of a research, so they would be prepared for an independent empirical work. During the semester students have to manage work with a statistical software - from creating the data matrix and saving it to making the univariant and bivariant analysis. The course prepares students for writing an emipirical Bachelor or Master dissertation.
The course is taught in English.
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Requirements on student
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The processing of learning tasks is the essential part of this course.The learning tasks are controlled continuously by teacher. Texts for study are elaborated in required form (essay, presentation, resume, synopsis, abstract). Test.
Students have good knowledge of taught literature.
Students elaborate:
- critical reflexions of assigned literature
- own research proposal
- data collection report/ technical information
- own data analyses
- research report
Students prompt research proposals of their colleagues.
Students obtain appropriate data autonomously.
Students present draft of reserch report.
Students prompt draft research reports of their colleagues.
Students defend their final research report.
The course is taught in English.
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Content
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- types and sources of data
- tabular data
- association
- interpretation of data
- STATA software
- data matrix
- putting-in data
- data management
- descriptive statistics in STATA
- Stat-Transfer software
- research report
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Activities
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Fields of study
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Guarantors and lecturers
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Literature
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Basic:
Acock, Alan C. A gentle introduction to STATA. College Station : Stata Press, 2006. ISBN 1-59718-009-2.
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Basic:
Hamilton, Lawrence C. Statistics with STATA : updated for version 9. Belmont : Brooks/Cole, 2006. ISBN 0-495-10972-X.
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Basic:
Becker, Howard Saul. Writing for social scientists : how to start and finish your thesis, book, or article. Chicago : University of Chicago Press, 1986. ISBN 0-226-04108-5.
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Extending:
Rabe-Hesketh, S., Everitt, B. A Handbook of Statistical Analyses Using Stata. (3rd. Ed.). Boca Raton. Chapman & Hall/CRC, 2004.
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Extending:
Fox, John. Applied regression analysis, linear models, and related methods. Thousand Oaks : SAGE Publications, 1997. ISBN 0-8039-4540-X.
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On-line library catalogues
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Time requirements
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All forms of study
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Activities
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Time requirements for activity [h]
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Preparation for formative assessments (2-20)
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16
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Preparation for an examination (30-60)
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60
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Undergraduate study programme term essay (20-40)
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40
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Contact hours
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52
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Individual project (40)
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40
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Total
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208
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Prerequisites - other information about course preconditions |
Good working knowledge of English.
Basic exposure to statistics: KSA/AAV or KSA/AAV1 or KSS/ZZD.
Intermediate knowledge of the methods of data collection: KSS/MV1 or KSA/MTV1.
The course is taught in English. |
Competences acquired |
Students are able to:
- formulate a research question
- suggest an appropriate research design
- choose an appropriate data
- obtain the appropriate data
- choose an appropriate data analytic method
- manage software STATA
- estimate potentialities of quantitative data analysis using software STATA
- analyse assigned quantitative data using software STATA
- create a simple bi-variate table/graph
- interpret obtained results
- present own analyses and their findings in a research report
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Teaching methods |
- Project-based instruction
- Students' portfolio
- Skills demonstration
- Task-based study method
- Individual study
- Textual studies
- Lecture
- Seminar
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Assessment methods |
- Test
- Project
- Seminar work
- Individual presentation at a seminar
- Combined exam
- Skills demonstration during seminar
- Continuous assessment
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