Course code Soci5040

Credit points 2

Processing of Sociological Information

Total Hours in Course80

Number of hours for lectures12

Number of hours for seminars and practical classes12

Independent study hours56

Date of course confirmation04.11.2020

Responsible UnitInstitute of Social Sciences and Humanities

Course developer

author lect.

Lana Janmere

Mg. sc. soc.

Prior knowledge

Soci5041, Social Research Methods

Course abstract

The study course provides in-depth knowledge and skills in the processing of sociological research results, which allow them to be correctly analysed and interpreted. Master students both theoretically and practically learn the most important descriptive and inferential statistical methods and their application in various designs of quantitative research, in which a survey is used as a data acquisition method. Master students gain an idea of the meaning of data-based conclusions, their making and interpretation, which allows to test existing and develop new knowledge in sociological theory. The practical classes of the study course are focused on the application of specific data processing methods in the collection and analysis of survey results. The study course promotes the development of critical thinking and personal competencies.

Learning outcomes and their assessment

Knowledge: The student knows and understands the essence of quantitative data processing and analysis in various quantitative research designs, knows the most suitable statistical processing methods for the survey data, the conditions of their use – practical works, independent work, test.
Professional skills: Able to independently create a research database and test it, able to collect survey data, obtain primary results and display them graphically, able to measure the closeness of the survey data, determine their statistical significance and compare group mean trends – practical works, independent work.
Soft skills: Ability to plan tasks responsibly, able to cooperate, engage in discussion and reasonably defend one's point of view, able to critically evaluate the obtained information and draw data-based conclusions - practical works, independent work, test, discussions.
Competence: Able to independently plan and implement quantitative data processing, analysis and drawing conclusions to gain new knowledge about the research problem, able to independently solve non-standard situations in the implementation of sociological research and the selection of appropriate data processing methods – independent work, test.

Course Content(Calendar)

1. Methods of obtaining quantitative data (1 hour).
2. An overview of the most popular computer programs used to process survey data. Data file preparation in IBM SPSS (1 hour).
3. Obtaining primary results for analyzing social tendencies in sociological researches (1 hour).
4. Descriptive study design. Interpretation of primary results in a descriptive study (1 hour).
5. Indicators for measuring the closeness of data relationships in analysis of social problems (2 hours).
6. Determining the statistical significance of the detected relationships in the data (2 hours).
7. Assessing group differences and comparing average trends (2 hours).
8. Quasi-experimental study design. Definition of independent and dependent variables, determination of their interaction using simple linear regression analysis (2 hours).

List of practical work:
1. Preparation of the research base, input and verification of survey data (3 hours).
2. Acquisition of primary results, their interpretation and reflection in graphic solutions (5 hours).
3. Measuring the closeness of data relationships, determining statistical significance and comparing average trends. Interpretation of the obtained results (4 hours).

Requirements for awarding credit points

2 practical works and 1 independent work must be elaborated. Written test at the end of the course.

Acquisition of the study course in distance learning is organized in accordance with the order of the Vice-Rector for Studies “On the procedure of e-studies at LLU”, a study course acquisition schedule is created for each semester. Students acquire the topics included in the study course independently, using the materials created and inserted by the lecturer in the e-learning environment Moodle. Feedback on the acquisition of topics in lectures and seminars in distance learning is organized in the form of self-examination tests, discussion forums and individual assignments, as well as face-to-face or online consultations, lectures and final examinations according to the schedule.

Description of the organization and tasks of students’ independent work

1. Practical work: Preparation of the research base, input and verification of survey data.
2. Practical work: Acquisition of primary results, their interpretation and reflection in graphic solutions.
3. Independent work: Measuring the closeness of data relationships, determining statistical significance and comparing average trends. Interpretation of the obtained results.
4. Written test at the end of the course.

Criteria for Evaluating Learning Outcomes

Test with a mark. Its evaluation consists of: practical work 1 (20%), practical work 2 (30%), independent work (30%), test (20%).

Compulsory reading

1. Babbie E., Halley F., Wagner W. E., Zaino J. Adventures in Social Research: Data Analysis Using IBM SPSS Statistics. Thousand Oaks, Calif.: Sage, 2013. 456 p.
2. Bourke J., Kirby A., Doran J. Survey & questionnaire design: Collecting Primary Data to Answer Research Questions: eBook. Ireland: NuBooks, 2016. 47 p. Retrieved from EBSCO eBook Academic Collection via LLU Fundamental library network.
3. Elst van H. Foundations of Descriptive and Inferential Statistics. Germany, 2019. 176 p. Elektroniski pieejama https://arxiv.org/pdf/1302.2525.pdf.
4. Greasley P. Quantitative Data Analysis Using SPSS. An Introduction for Health & Social Science. England: Open University Press, 2008. 146 p. Elektroniski pieejama https://knowledgegat.com.au/wp-content/uploads/2019/12/Analysis_SPSS.pdf.
5. Jansons V., Kozlovskis K. Mārketinga pētījumi: teorija un prakse SPSS 20 vidē. 1. daļa. Rīga, RTU izdevniecība, 2015. 400 p. Tiešsaistē pieejama https://dom.lndb.lv/data/obj/841728.html.
6. Sirkin R. M. Statistics for the Social Sciences. London: Sage Publications, 2005. 632 p.

Further reading

1. Arhipova I., Bāliņa S. Statistika ekonomikā un biznesā. Risinājumi ar SPSS un Microsoft Excel. Rīga: Datorzinību Centrs, 2006. 364 lpp.
2. Geske A., Grīnfelds A. Izglītības pētniecība. Rīga: LU Akadēmiskais apgāds, 2006. 261 lpp.
3. Jansons V., Kozlovskis K. Mārketinga pētījumi: teorija un prakse SPSS 20 vidē. 2. daļa. Rīga: RTU izdevniecība, 2016. 326 lpp. Tiešsaistē pieejama https://dom.lndb.lv/data/obj/841729.html.
4. Jansons V., Kozlovskis K. Mārketinga pētījumi: teorija un prakse SPSS 20 vidē. 3. daļa. Rīga: RTU izdevniecība, 2018. 290 lpp. Tiešsaistē pieejama https://dom.lndb.lv/data/obj/841730.html.
5. Lasmanis A. Datu ieguves, apstrādes un analīzes metodes pedagoģijas un psiholoģijas pētījumos. 1. grāmata. Rīga: SIA “Izglītības soļi”, 2002. 236 lpp.
6. Lasmanis A. Datu ieguves, apstrādes un analīzes metodes pedagoģijas un psiholoģijas pētījumos. 2. grāmata. Rīga: SIA “Izglītības soļi”, 2002. 422 lpp.

Periodicals and other sources

1. European Societies - European Sociological Association, UK. Pieejams: http://www.europeansociology.org/index.php?option=com_content&task=view&id=48&Itemid=29
2. International Journal of Social Research Methodology. Pieejams: http://www.tandfonline.com/loi/tsrm20
3. R Programming Tutorial - Learn the Basics of Statistical Computing. Pieejams: https://www.youtube.com/watch?v=_V8eKsto3Ug
4. Statistics - A Full University Course on Data Science Basics. Pieejams: https://www.youtube.com/watch?v=xxpc-HPKN28

Notes

Mandatory study course in the ESAF academic master's study program "Sociology of Organizations and Public Administration".