FSS:ZUR565 Statistical data analysis - Course Information
ZUR565 Statistical data analysis
Faculty of Social StudiesSpring 2018
- Extent and Intensity
- 1/1/0. 6 credit(s). Type of Completion: z (credit).
- Teacher(s)
- Mgr. Lenka Dědková, Ph.D. (lecturer)
doc. Mgr. et Mgr. Hana Macháčková, Ph.D. (lecturer) - Guaranteed by
- Mgr. et Mgr. Marína Urbániková, Ph.D.
Department of Media Studies and Journalism – Faculty of Social Studies
Contact Person: Ing. Bc. Pavlína Brabcová
Supplier department: Department of Media Studies and Journalism – Faculty of Social Studies - Timetable
- Thu 15:15–16:45 PC54
- Prerequisites (in Czech)
- ZUR559 Methods and technigues || NOW( ZUR559 Methods and technigues )
- Course Enrolment Limitations
- The course is only offered to the students of the study fields the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 0/20, only registered: 0/20 - fields of study / plans the course is directly associated with
- Media Studies and Journalism (programme FSS, N-KS)
- Course objectives
- The course will provide introduction into the statistical analysis in media research. It will focus on the logic and principles behind statistical analysis and interpretation as well as the work with the SPSS software.
- Learning outcomes
- The students will require following skills: - work with diverse data files and diverse types of variables in SPSS software (data cleaning procedure, transformation and creation of the variables, cases selection etc.) - statistical analysis procedure (understanding inferential statistics and hypotheses testing, univariate and bivariate analyses)
- Syllabus
- 1. Course introduction. Sylabus and requirements for course fulfillment. 2. Introduction into quantitative research, character of diverse data. Variables types and attributes. Basic introduction into SPSS software. Work with data in SPSS: variable creation and editing. 3. Data cleaning procedure. Distribution of categorical and scaled data. 4. Variable transformation and computation, work with diverse variable types. 5. Practical seminar. 6. Normal distribution, hypotheses testing and inferential statistic. 7. Bivariate analysis 1: categorical data. Crosstabulation. 8. Bivariate analysis 2: scaled variables. Correlations. 9. No lecture - Faculty day. 10. Mean comparison between groups. T-test and ANOVA. 11. Practical seminar. 12. Other advanced techniques: Multivariate analysis. 13. Practical seminar.
- Literature
- required literature
- FIELD, Andy P. Discovering statistics using IBM SPSS statistics : and sex and drugs and rock 'n' roll. 4th edition. Los Angeles: Sage, 2013, xxxvi, 915. ISBN 9781446249178. info
- Teaching methods
- Lectures and practical seminars.
- Assessment methods
- Course requirements: 1. Active participation with maximum of 2 absences 2. Submission of 7 home-tasks, max. 30 points (minimum 15 points) 3. Final exam, max. 70 points (minimum 42 points)
- Language of instruction
- Czech
- Enrolment Statistics (Spring 2018, recent)
- Permalink: https://is.muni.cz/course/fss/spring2018/ZUR565