Quantitative Social Data Analysis Methods
Course: Sociology
Structural unit: Faculty of Sociology
Title
Quantitative Social Data Analysis Methods
Code
ОК14
Module type
Обов’язкова дисципліна для ОП
Educational cycle
First
Year of study when the component is delivered
2023/2024
Semester/trimester when the component is delivered
4 Semester
Number of ECTS credits allocated
8
Learning outcomes
1.1 Know for which problems each of the methods of data analysis is used to solve.
1.2 Know the conditions and limitations of using each of the methods, including data requirements.
2.1 Be able to prepare empirical data in the electronic format necessary for the application of the method of analysis.
2.2 Be able to use specialized computer programs (software systems) to analyze data of empirical sociological research.
2.3 Be able to interpret the results of computer analysis and draw grounded conclusions based on these results.
2.4 Be able to present the results of empirical data analysis in reports, scientific publications, presentations for a professional audience.
Form of study
Full-time form
Prerequisites and co-requisites
Students should be familiar with the basic concepts of probability theory and practical skills of working with a personal computer in a Windows environment.
Course content
1. Application of mathematical methods in sociology.
2. Measurement of social variables. Measurement levels.
3. Descriptive statistics. Frequencies tables. Central tendency and variation.
4. Bivariate analysis. Cross-tables. The measure of association.
5. Correlation analysis.
6. Linear regression model.
7. Sampling method in sociological research.
8. Statistical inference. Point and interval estimation.
9. Statistical hypotheses testing.
10. Cluster analysis.
11. Factor analysis.
12. Analysis of the reliability of the additive scale.
13. Presentation of the results of empirical data analysis.
Recommended or required reading and other learning resources/tools
1. Paniotto V., Maksymenko V., Kharchenko N. Statistical analysis of sociological data, 2004 (in Ukrainian) pp. 10-168, 177-241
2. Sociology: a short encyclopedic dictionary, 1998 (in Ukrainian).
3. Gorbachyk A.P., Salnikova S.A. Data Analysis in Sociological Research Using SPSS (in Ukrainian). pp. 24-78, 112-146
4. Eric J. Krieg E.J. Statistics and Data Analysis for Social Science. - Pearson Education Limited, 2014. – 392 p. – pp. 1-138, 203-280, 309-344
Planned learning activities and teaching methods
Lecture, practical training, personal work
Assessment methods and criteria
3 semester
1. Test work 1 for topics 1-3, LO1.1, LO1.2, LO2.2 – 12 points / 20 points
2. Test work 2 for topics 4-6, LO1.1, LO1.2, LO2.2, LO2.3 – 12 points / 20 points
3. Performing tasks in training classes on topics 1-6, LO1.2, LO2.1, LO2.2, LO2.3 – 36 points / 60 points
final assessment - credit
4 semester
1. Test work 3 for topics 7-10, LO1.1, LO1.2, LO2.2, LO2.3 – 12 points / 20 points
2. Personal work on data analysis for topics 7-11, compulsory, LO1.1, LO1.2, LO2.1, LO2.2, LO2.3, LO2.4 – 12 points / 20 points
3. Performing tasks in training classes on topics 7-13, LO1.1, LO1.2, LO2.1, LO2.2, LO2.3, LO2.4 – 12 points / 20 points
final assessment – exam for topics 1-13, LO1.1, LO1.2, LO2.1, LO2.2, LO2.3, LO2.4; the grade for the discipline is a grade in the 4th semester..
Language of instruction
ukrainian
Lecturers
This discipline is taught by the following teachers
Departments
The following departments are involved in teaching the above discipline