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Methods of Mathematical Statistics in Social Sciences
Study Course Description
Course Description Statuss:Approved
Course Description Version:5.00
Study Course Accepted:30.04.2024 09:11:30
| Study Course Information | |||||||||
| Course Code: | DN_199 | LQF level: | Level 8 | ||||||
| Credit Points: | 2.00 | ECTS: | 3.00 | ||||||
| Branch of Science: | Mathematics | Target Audience: | Information and Communication Science; Social Welfare and Social Work; Political Science; Management Science; Law; Social Anthropology; Sociology | ||||||
| Study Course Supervisor | |||||||||
| Course Supervisor: | Andrejs Ivanovs | ||||||||
| Study Course Implementer | |||||||||
| Structural Unit: | Department of Doctoral Studies | ||||||||
| The Head of Structural Unit: | |||||||||
| Contacts: | Riga, 16 Dzirciema Street, dn rsu[pnkts]lv, +371 67409120 | ||||||||
| Study Course Planning | |||||||||
| Full-Time - Semester No.1 | |||||||||
| Lectures (count) | 2 | Lecture Length (academic hours) | 2 | Total Contact Hours of Lectures | 4 | ||||
| Classes (count) | 4 | Class Length (academic hours) | 3 | Total Contact Hours of Classes | 12 | ||||
| Total Contact Hours | 16 | ||||||||
| Study course description | |||||||||
| Preliminary Knowledge: | Knowledge in mathematics and informatics. | ||||||||
| Objective: | To provide knowledge about the use of statistical concepts in social sciences taking into account the development of digitalisation, to independently find the necessary data, group and analyse them using appropriate methods and to develop an understanding of the practical use of the obtained data in the presentation of the obtained results in the study. | ||||||||
| Topic Layout (Full-Time) | |||||||||
| No. | Topic | Type of Implementation | Number | Venue | |||||
| 1 | The role of statistics in the research process. Descriptive statistics and inferential statistics. Principles of hypothesis testing with P-value and confidence intervals. | Lectures | 1.00 | E-Studies platform | |||||
| 2 | Types of data and measurement scales. Normal distribution. Vast range of statistical methods. | Lectures | 1.00 | auditorium | |||||
| 3 | Preparing data for IBM SPSS Statistics. Descriptive statistics, inferential statistics and visualization of data for proportion analysis. | Classes | 1.00 | computer room | |||||
| 4 | Selection of descriptive statistics, inference statistics, and visualization for quantitative data (and data on an ordinal scale) for comparison of two or more samples. | Classes | 1.00 | computer room | |||||
| 5 | The use of correlation, linear regression and binary logistic regression analysis. Scale reliability analysis | Classes | 1.00 | computer room | |||||
| 6 | Sample size calculation in different types of research. Practical work: description of statistical methods that will be used in research. | Classes | 1.00 | computer room | |||||
| Assessment | |||||||||
| Unaided Work: | 1. Creating the table with names of variables, examples of data and their corresponding measurement scales of the current or planned research. 2. Reading literature from the list of Required reading according to topics of lectures and classes. 3. Reviewing examples of descriptions of statistical methods used in scientific publications. The student's contribution to the improvement of the study process is the provision of meaningful feedback on the study course by filling out its evaluation questionnaire. | ||||||||
| Assessment Criteria: | Participation in lectures and classes, a written description of statistical analysis of own research data (100%). | ||||||||
| Final Examination (Full-Time): | Test | ||||||||
| Final Examination (Part-Time): | |||||||||
| Learning Outcomes | |||||||||
| Knowledge: | On successful completion of the study course, students are able to identify knowledge that will allow to recognise the statistical terminology and the basic methods used in various publications. | ||||||||
| Skills: | Upon successful completion of the study course, students will be able to Correctly identify, prepare and enter data in the IBM SPSS Statistics. Analyse and create and edit tables and charts; systematise and select appropriate methods of data processing, incl. performing statistical hypotheses testing. | ||||||||
| Competencies: | On successful completion of the study course, students will be able to correctly interpret the most important statistical indicators and to use the acquired basic statistical methods in the study data processing. | ||||||||
| Bibliography | |||||||||
| No. | Reference | ||||||||
| Required Reading | |||||||||
| 1 | Nahm, F. S. 2016. Nonparametric statistical tests for the continuous data: the basic concept and the practical use. Korean J. Anesthesiol. 69(1): 8–14. DOI: 10.4097/kjae.2016.69.1.8 (Tiešsaistē) | ||||||||
| 2 | SPSS for Social Scientists. 2009. Red Globe Press; 9th Edition. | ||||||||
| 3 | IBM SPSS for Intermediate Statistics Use and Interpretation. 2015. 5th Edition. By Nancy L. Leech, Karen C. Barrett, George A. Morgan. | ||||||||
| 4 | Field, A. 2018. Discovering Statistics using IBM SPSS Statistics. 4th Edition, Sage Publications. | ||||||||
| Additional Reading | |||||||||
| 1 | Laerd Statistics. | ||||||||
