ZURn6302 Statistical Analysis

Faculty of Social Studies
Autumn 2024
Extent and Intensity
1/1/0. 8 credit(s). Type of Completion: zk (examination).
In-person direct teaching
Teacher(s)
Mgr. Lenka Dědková, Ph.D. (lecturer)
Mgr. Michaela Šaradín Lebedíková, Ph.D. (seminar tutor)
Guaranteed by
Mgr. Lenka Dědková, Ph.D.
Department of Media Studies and Journalism – Faculty of Social Studies
Contact Person: Mgr. Boris Rafailov, Ph.D.
Supplier department: Department of Media Studies and Journalism – Faculty of Social Studies
Timetable
Fri 10:00–11:40 PC25
Prerequisites
ZURn4108 Analysis of Quantitative Data
The prerequisite for enrolling in the course is the completion of the course ZUN108 Descriptive analysis of quantitative data.
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course will provide introduction into the inferential 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. The course is taught in Czech.
Learning outcomes
Students will be able to:
- understand the assumptions in statistics (probabilities, descriptive and inferential statistics, hypotheses testing, effect sizes)
- conduct basic analyses (t-tests, ANOVA, correlations, regression)
Syllabus
  • The course will cover the following topics (the specific order may vary): - Course introduction. Syllabus and requirements for course fulfillment, SPSS, syntax.
  • - Normal distribution, hypotheses testing, and inferential statistic.
  • - Bivariate analysis 1: categorical data. Crosstabulation.
  • - Bivariate analysis 2: continuous variables. Correlations.
  • - Mean comparison between groups. T-test, ANOVA. ANCOVA.
  • - Linear regression.
  • - Scales.
  • - Logistic regression.
  • - Introduction to other analytical options: mediation, moderation, longitudinal analyses, multilevel analyses, structural equation modeling.
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, Texts, 2014, xxxvi, 915. ISBN 9789351500827. info
    recommended literature
  • BERKMAN, Elliot T. and Steven Paul REISE. A conceptual guide to statistics using SPSS. Los Angeles: Sage, 2012, xiii, 296. ISBN 9781412974066. info
Teaching methods
Lectures and practical seminars.
Assessment methods
attendance, home assignments, final exam

Evaluation based on interim tasks and final test, with a maximum of 100 points. Grading:
A 100-90
B 89-80
C 79-70
D 69-60
E 59-50
F 49-0

Attendance: mandatory attendance at 75% of seminars (8 out of 11)

Homeworks: A total of 8 homework for which a maximum of 35 points can be obtained. The condition for completing the course is to submit all assignments and obtain at least 17 points for their evaluation. Assignments are always handed in by Wednesday 12:00 before the lecture following the assignment (i.e. there are 5 days to complete the assignment).

Final test: A maximum of 65 points can be obtained.
Language of instruction
Czech
Further Comments
The course is taught annually.
The course is also listed under the following terms Autumn 2020, Autumn 2021, Autumn 2022, Autumn 2023.
  • Enrolment Statistics (recent)
  • Permalink: https://is.muni.cz/course/fss/autumn2024/ZURn6302