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Analysis of Categorical Data
Major: Sociology
Code of subject: 7.054.01.O.002
Credits: 5.00
Department: Sociology and Social Work
Lecturer: PhD, Romana Myshok
Semester: 1 семестр
Mode of study: денна
Завдання: ZK01. Ability to abstract thinking, analysis and synthesis.
SK01. Ability to analyze social phenomena and processes.
SK04. Ability to collect and analyze empirical data using modern methods of sociological research.
Learning outcomes: PR01. Analyze social phenomena and processes using empirical data and modern concepts and theories of sociology.
PR02. Diagnose and interpret social problems of Ukrainian society and the world community, their causes and consequences.
PR03. Develop and implement social and interdisciplinary projects taking into account social, economic, legal, environmental and other aspects of social life.
PR04. Apply scientific knowledge, sociological and statistical methods, digital technologies, specialized software to solve complex problems of sociology and related fields of knowledge.
PR05. Search, analyze and evaluate the necessary information in scientific literature, data banks and other sources.
PR06. Communicate freely orally and in writing in Ukrainian and one of the foreign languages when discussing professional issues, research and innovations in the field of sociology and related sciences, including in the context of cooperation with European and Euro-Atlantic institutions.
PR07. To solve ethical dilemmas in accordance with the norms of professional ethics of a sociologist and universal human values.
PR08. It is clear and unambiguous to convey knowledge, own conclusions and arguments on issues of sociology and related fields of knowledge to specialists and non-specialists, in particular to persons who are studying.
PR09. Plan and carry out scientific research in the field of sociology, analyze the results, justify the conclusions.
Zn1 Specialized conceptual knowledge,
which include modern scientific achievements in the field of professional activity or field of knowledge and are the basis for original thinking and conducting research
Zn2 Critical understanding of problems in the field and on the border of the fields of knowledge
М1 Specialized skills/problem-solving skills necessary for conducting research and/or carrying out innovative activities in order to develop new knowledge and procedures
Mind2 Ability to integrate knowledge and solve complex problems in broad or multidisciplinary contexts
K2 Use of foreign languages in professional activities
AB1 Management of work or learning processes that are complex, unpredictable and require new strategic approaches
AB3 Ability to continue learning with a high degree of autonomy
Required prior and related subjects: • Methodology of Discourse Analysis;
• Modern Ukrainian Society as a Society of Risk;
• Analytical Sociology in Management Processes;
• Social Communications in Public Administration;
• Modern Ukrainian Society: Sociological Analysis.
Summary of the subject: The course "Analysis of Categorical Data" involves students learning the most important provisions and theoretical schemes of the analytical component of sociological research, as well as familiarization with the possibilities of using modern software in sociological research.
Studying the course involves the student's work in lectures, practical classes, studying the recommended literature, writing an individual calculation paper based on the calculation and interpretation of basic indicators related to the analysis of categorical variables. When studying theoretical provisions, interactive forms of teaching should dominate. As a result, students should learn the basics of quantitative analysis of categorical features.
Опис: Analysis of one categorical variable. Types of categorical variables. Coding categorical variables. Frequency analysis of categorical variables. Descriptive statistics for nominal and ordinal data. Models of two categorical variables dependencies. The basic models of two nominal variables dependencies. Odds of two nominal variables dependencies. Construction and analysis of two-dimensional tables. Factor analysis. Cluster analysis. The approaches to the analysis of multidimensional tables.
Assessment methods and criteria: The evaluation of students of education in the discipline is carried out with the help of means of objective control of the degree of achievement of learning results.
1. The evaluation is carried out on the basis of the assessment of the level of competences achieved and the results of the bachelor’s studies in the specialty "Sociology", using the methods of complex diagnostics: the semester control (SC) of the knowledge of the students of education is carried out based on the total number of points obtained according to the results of the current control (PC), and the implementation control measure (KZ).
2. The information base, on the basis of which the means of objective control of the degree of achievement of learning results are formed, is its subject matter, tasks for practical and individual works, a list of literature and methodical recommendations.
3. Assessment of the level of achievement of learning outcomes is carried out after the students complete the work program in its entirety.
Критерії оцінювання результатів навчання: • current control: written reports on laboratory work, oral examination, individual work (40%);
• final control (control measure, test): writing (60%).
Recommended books: 1. Paniotto, V.I., Maksymenko, V.S. & Kharchcenko N.M. (2004) Statystychnyi analiz sotsiolohichnykh danykh. – K.: Vyd. dim «КМ Akademiia» (in Ukrainian);
2. Horbachyk, A. P. (2008) Analiz danyh sotsiolohichnyh doslidzhen zasobamy SPSS: Navch. posib. Lutsk : RVV «Vezha» Volyn. nats. univers. im. Lesi Ukrainky (in Ukrainian);
3. Keuschnigg, M., Lovsjo, N. & Hedstrom, P. (2017). Analytical Sociology and Computational Social Science. Journal of Computational Science. DOI: 10.1007/s42001-017-0006-5.
4. Cruz, M. S.-G., Cilleros, M., Victoria, M. & Sanchez, G. (2019). Evaluation of Computer Assisted Qualitative Data Analysis Software (CAQDAS) Applied to Research. DOI: 10.1007/978-3-030-20798-4_41.
5. Edelmann, A., Wolff, T., Montagne, D. & Bail, C. A. (2020) Computational Social Science and Sociology. Annual Review of Sociology, 46(1). DOI: 10.1146/annurev-soc-121919-054621