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Research Data Analysis
Study Course Description
Course Description Statuss:Approved
Course Description Version:3.00
Study Course Accepted:17.06.2022 15:50:50
| Study Course Information | |||||||||
| Course Code: | SL_030 | LQF level: | Level 7 | ||||||
| Credit Points: | 2.00 | ECTS: | 3.00 | ||||||
| Branch of Science: | Mathematics; Theory of Probability and Mathematical Statistics | Target Audience: | Rehabilitation; Psychology | ||||||
| Study Course Supervisor | |||||||||
| Course Supervisor: | Diāna Kalniņa | ||||||||
| Study Course Implementer | |||||||||
| Structural Unit: | Statistics Unit | ||||||||
| The Head of Structural Unit: | |||||||||
| Contacts: | Baložu iela 14, Block A, Riga, +371 67060897, statistika rsu[pnkts]lv, www.rsu.lv/statlab | ||||||||
| Study Course Planning | |||||||||
| Full-Time - Semester No.1 | |||||||||
| Lectures (count) | 6 | Lecture Length (academic hours) | 2 | Total Contact Hours of Lectures | 12 | ||||
| Classes (count) | 6 | Class Length (academic hours) | 2 | Total Contact Hours of Classes | 12 | ||||
| Total Contact Hours | 24 | ||||||||
| Study course description | |||||||||
| Preliminary Knowledge: | Bachelor's experience in research and knowledge in research methodology. | ||||||||
| Objective: | To enhance MA students' comprehension of the quantitative and qualitative data processing methods; to improve the data processing skill; to develop the ability of independent decision-making about the use of suitable data processing methods in the respective situation for proving the set hypotheses or the clarification of a study issue. | ||||||||
| Topic Layout (Full-Time) | |||||||||
| No. | Topic | Type of Implementation | Number | Venue | |||||
| 1 | Introduction to data analysis. Differences in qualitative and quantitative designs. Data analysis in quantitative and qualitative designs. | Lectures | 1.00 | auditorium | |||||
| Classes | 1.00 | auditorium | |||||||
| 2 | Data input and preparation for analysis. | Lectures | 1.00 | auditorium | |||||
| Classes | 1.00 | auditorium | |||||||
| 3 | Data analysis in qualitative design: qualitative content analysis, thematic analysis, integrative phenomenological analysis (IPA). | Lectures | 2.00 | auditorium | |||||
| Classes | 2.00 | auditorium | |||||||
| 4 | Data analysis in quantitative design: descriptive and inferential statistics. | Lectures | 1.00 | auditorium | |||||
| Classes | 1.00 | auditorium | |||||||
| 5 | Correct description and visualisation of results in quantitative and qualitative design. | Lectures | 1.00 | auditorium | |||||
| Classes | 1.00 | auditorium | |||||||
| Assessment | |||||||||
| Unaided Work: | To read the indicated sources of literature independently. To perform the assigned tasks on data processing independently. | ||||||||
| Assessment Criteria: | Independent processing of own data, description and presentation of the obtained results in a group. | ||||||||
| Final Examination (Full-Time): | Exam (Written) | ||||||||
| Final Examination (Part-Time): | |||||||||
| Learning Outcomes | |||||||||
| Knowledge: | Students use the terminology that is suitable for the research strategy (mathematical statistics terminology/qualitative research terminology); explain differences between different data processing methods; mention and characterise the data processing methods that apply to different research designs. | ||||||||
| Skills: | Process research data; analyse the statistical indicators; in compliance with the set hypothesis/research question, correctly describe the obtained results. | ||||||||
| Competencies: | Apply the data processing methods that are appropriate for the particular research design; analyse and interpret the results of data processing; formulate correct conclusions concerning the approval or rejection of the hypotheses, put forward in the study, or about research questions. | ||||||||
| Bibliography | |||||||||
| No. | Reference | ||||||||
| Required Reading | |||||||||
| 1 | Mārtinsone, K., Pipere, A. un Kamerāde, D. (red.). (2016). Pētniecība: teorija un prakse. Rīga: RaKa. | ||||||||
| 2 | Kroplijs, A. un Raščevska, M. (2010). Kvalitatīvās pētniecības metodes sociālajās zinātnēs. Rīga: RaKa. (akceptējams izdevums) | ||||||||
| 3 | Raščevska, M. un Kristapsone, S. (2000). Statistika psiholoģijas pētījumos. Rīga: Izglītības soļi. (akceptējams izdevums) | ||||||||
| 4 | Mārtinsone, K., Perepjolkina, V. un Šneidere, K. (red.) (2020). Metodiskie norādījumi maģistra darbu izstrādei RSU veselības psiholoģijas un supervīzijas studiju programmām. Otrais, atjaunotais izdevums. | ||||||||
| Additional Reading | |||||||||
| 1 | Leavy, P. (ed.) (2014). The Oxford Handbook of Qualitative Research. New York: Oxford University Press. | ||||||||
| 2 | SPSS for social scientists /Acton C., et.al./ Basingstoke: Palgrave Macmillan (2009). 363 lpp. | ||||||||
| Other Information Sources | |||||||||
| 1 | Choosing the Correct Statistical Test in SAS, STATA and SPSS. | ||||||||
