Infopaket

Quantitative Social Data Analysis Methods

ОК16

Обов’язкова дисципліна для ОП

First

2021/2022

4 Semester

9

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.

Full-time form

Students should be familiar with the basic concepts of probability theory and practical skills of working with a personal computer in a Windows environment.

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. 14. Using SPSS syntax language 15. Visualization of data and data analysis results.

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

Lecture, practical training, personal work

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..

ukrainian