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Main menu for Browse IS/STAG
Course info
KSS / KVAZ
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Course description
Department/Unit / Abbreviation
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KSS
/
KVAZ
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Academic Year
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2023/2024
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Academic Year
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2023/2024
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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,
7
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]
Tutorial
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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Czech
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Occ/max
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|
|
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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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9 / -
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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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Czech
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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 |
Yes
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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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N/A
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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.
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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).
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.
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Content
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1. types and sources of data
2. tabular data
3. association
4. interpretation of data
5.-6. STATA software
7. data matrix
8. putting-in data
9.-10. data management
11. descriptive statistics in STATA
12. Stat-Transfer software
13. research report
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Activities
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Fields of study
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Základní informace a studijní materiály můžete najít na CourseWare předmětu KSS/KVAS.
https://portal.zcu.cz/portal/studium/courseware/kss/kvas/zaverecna_prace.html
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Guarantors and lecturers
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Guarantors:
PhDr. Mgr. František Kalvas, Ph.D. (100%),
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Lecturer:
Mgr. Patrik Galeta, Ph.D. (100%),
PhDr. Mgr. František Kalvas, Ph.D. (100%),
PhDr. Eva Krulichová, Ph.D. (100%),
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Tutorial lecturer:
PhDr. Eva Krulichová, Ph.D. (100%),
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Seminar lecturer:
Mgr. Patrik Galeta, Ph.D. (100%),
PhDr. Mgr. František Kalvas, Ph.D. (100%),
PhDr. Eva Krulichová, Ph.D. (100%),
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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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Recommended:
Rabe-Hesketh, S., Everitt, B. A Handbook of Statistical Analyses Using Stata. (3rd. Ed.). Boca Raton. Chapman & Hall/CRC, 2004.
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Recommended:
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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Individual project (40)
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40
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Undergraduate study programme term essay (20-40)
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24
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Contact hours
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78
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Preparation for an examination (30-60)
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40
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Total
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182
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Prerequisites
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Knowledge - students are expected to possess the following knowledge before the course commences to finish it successfully: |
to describe and explain the basic sociological methods |
to describe the formation of sociological perspectives in the use of sociological methods |
to enumerate and describe the basic quantitative methods |
to describe the basic knowledge resulting from empirical quantitative research |
Skills - students are expected to possess the following skills before the course commences to finish it successfully: |
to form a formally acceptable professional output |
to use foreign databases of professional journals |
to apply and interpret knowledge resulting from the application of quantitative methods |
to use adequate concepts corresponding terminology of the field in Czech and English |
Competences - students are expected to possess the following competences before the course commences to finish it successfully: |
N/A |
N/A |
N/A |
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Learning outcomes
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Knowledge - knowledge resulting from the course: |
to enumerate and describe key studies and requisites corresponding with the topic of quantitative research |
to describe and intepret theoretical approaches used during quantitative research |
to describe and interpret methods used during quantitative research |
Skills - skills resulting from the course: |
to sort key knowledge resulting from quantitative research |
to demonstrate and apply selected research methods used during quantitative research |
to critically evaluate the acquired knowledge |
Competences - competences resulting from the course: |
N/A |
N/A |
N/A |
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Assessment methods
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Knowledge - knowledge achieved by taking this course are verified by the following means: |
Combined exam |
Skills demonstration during practicum |
Seminar work |
Individual presentation at a seminar |
Continuous assessment |
Project |
Skills - skills achieved by taking this course are verified by the following means: |
Combined exam |
Skills demonstration during practicum |
Seminar work |
Individual presentation at a seminar |
Continuous assessment |
Project |
Competences - competence achieved by taking this course are verified by the following means: |
Combined exam |
Skills demonstration during practicum |
Individual presentation at a seminar |
Project |
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Teaching methods
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Knowledge - the following training methods are used to achieve the required knowledge: |
Lecture |
Seminar |
Task-based study method |
Textual studies |
Skills demonstration |
Project-based instruction |
Individual study |
Students' portfolio |
Skills - the following training methods are used to achieve the required skills: |
Lecture |
Seminar |
Task-based study method |
Textual studies |
Skills demonstration |
Individual study |
Project-based instruction |
Students' portfolio |
Competences - the following training methods are used to achieve the required competences: |
Skills demonstration |
Project-based instruction |
Students' portfolio |
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