VSFS:N_AEMD Media Data Analysis - Course Information

N_AEMD Social Knowledge and Media Data Analysis

Extent and Intensity

0/2/0. 6 credit(s). Type of Completion: zk (examination).

Teacher(s)

Mgr. Iva Baslarová, Ph.D. (seminar tutor)
Mgr. Michal Tomčík, PhD. (seminar tutor)

Guaranteed by

Mgr. Michal Tomčík, PhD.
Subdepartment of Management and Marketing – Department of Economics and Management – Departments – University of Finance and Administration
Contact Person: Lenka Pokorná

Prerequisites

There are no prerequisites for this course. Previous attandance to N_VSVM-course (NA_SRUM-course) is beneficial.

Course Enrolment Limitations

The course is offered to students of any study field.

Course objectives

The principal aim of this course is to introduce students to the basic and advanced statistical analyses of various sociological and media questionnaire surveys, to understand and interpret the outcomes of these analyses in both theoretical and practical context. From the theoretical point of view we will discuss the structure of data sets, character of various variables and type of right chosen statistical procedure. From the practical point of view the emphasis will be put on the use of statistical programme (Analytical tools in MS Excel), the application of basic and multidimensional analyses with data sets and learning how to interpret and present the results. Students who successfully complete the course will not be scared of data analyses yet, will be capable of using basic and some advanced statistical operation with variables from data sets, will be able to test statistical hypotheses by yourself, will gain a lot of theoretical and practical knowledge in the field of sociological, marketing and media survey and will gain the ability to use research techniques at user and problem solving level. It is assumed these knowledge will be developed in optional subject where the focus will be put on the statistical origin of analyses and other multidimensional methods.

Learning outcomes

After passing the course students will be able to:
- apply methods of media research on marketing topics,
- identify a quality and relevance of a research done by someone else,
- decide on the design and technique of the research when understanding media as organisations, contents or audiences,
- prepare a research design in a group,
- do/realize a research (data collection),
- DATA PROCESSING AND ANALYSIS (with Excel - Analytical tools),
- analyse collected data and interpret them in the context of own research aim,
- write a research report.

Syllabus

• 1. Research topic selection. Research groups constitution. 2. Research question and research hypotheses formulation. 3. Operationalistion - how hypotheses become variables (questionnaire questions or codes and categories in Content Analysis) 4. Principal characteristics of sociological survey data, structure of data file and its appearance in SPSS and Excel (Analytical tool). Types of hypotheses, elementary rules for the formulation of hypotheses and their testing on survey data. 5. Types of variable (nominal, ordinal, continuous), basic rules the choice of right statistical procedure appropriate to types of variables to be analyzed. 6. Distributions of nominal and ordinal variables, their principal characteristics. 7. Distributions of continuous variables, their principal characteristics. 8. Transformations of variables, basic principles of generating new variables , recoding existing variables, handling missing values. Selecting specific cases (subsamples) for analyses. 9. Normal distribution, its main properties, principles of hypotheses testing based on normal distribution, population and samples, types of samples, statistical inference. 10.Principles of analyses of variance, components of variance (total, between groups, within groups), comparing groups testing hypotheses about equality of means using analysis of variance. 11. Principles of analyses based on categorical (nominal, ordinal) variables, crosstabulations, right choice among measures of association for different types of variables. 12. Principles of analyses of associations between continuous variables (covariance, correlations). How to assess other than linear associations between variables with non-normal distributions.

Literature

required literature
• Mareš, P., L. Rabušic, P. Soukup. 2015. Analýza sociálněvědních dat (nejen) v SPSS. MUNIPRESS, Brno, ISBN: 978-80-210-6362-4
• Sedláková, R. 2015. Výzkum médií: Nejužívanější metody a techniky. Praha: Grada. ISBN: 978-80-247-3568-9

recommended literature
• Pallant, J.: SPSS Survival Manual: A step by step guide to data analysis using SPSS. Open University Press, 2010.
• Bryman, A., C. Cramer: Quantitative Data Analysis with IBM SPSS 17, 18 & 19: A Guide for Social Scientists. Routledge, 2011.
• Collier, J. Using SPSS Syntax: A Beginner's Guide. Sage Publications, 2009.

Teaching methods

Lectures and seminars in full-time study, tutorials in part-time study; compulsory seminar participation is 75% in full-time study, compulsory tutorial participation is 50% in part-time study. Every topic will be covered by a lecture and a seminar. Lectures will be based on presentations of individual topics by the lecturer followed by a discussion. Seminars will be based on presentations of assignments prepared by the students and mainly by data analysis.

Assessment methods

a) To get a credit (which is a pre-requisite for the oral examination) student is required: 1.To attend seminars (min. 75 %) and present there at least two times the results of assigned analyses. 2.To pass the final test assessing capability to run assigned analyses and interpreting their results. b) To pass the examination student will be required to submit in a due time a course final paper on the selected topic (list of topics will be provided by the instructor at the end of the semester). The paper will answer the analytical questions. Students will choose analytical tools (statistical procedures) to answer the questions (the appropriateness of the chosen procedure will the main be part of the paper evaluation), run the analysis, present and interpret the results. The paper will consist of: 1. Discussion of the method (SPSS procedure) chosen for the analysis (why the particular procedure was chosen). 2. Tables and/or graphs presenting the main results (selected results answering analytical questions). 3. Interpretation of results. 4. Appendix 1: A complete SPSS syntax for the performed analyses 5. Appendix 2: A complete SPSS outputs from the analyses.

Language of instruction

Czech

Further comments (probably available only in Czech)

The course can also be completed outside the examination period.
Information on the extent and intensity of the course: 10 hodin KS/semestr.

• Enrolment Statistics (recent)
  
• Permalink: https://is.vsfs.cz/course/vsfs/summer2021/N_AEMD