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Research Data Processing
Study Course Description
Course Description Statuss:Approved
Course Description Version:4.00
Study Course Accepted:12.08.2022 11:09:54
| Study Course Information | |||||||||
| Course Code: | SL_010 | LQF level: | Level 6 | ||||||
| Credit Points: | 2.00 | ECTS: | 3.00 | ||||||
| Branch of Science: | Mathematics; Theory of Probability and Mathematical Statistics | Target Audience: | Public Health | ||||||
| Study Course Supervisor | |||||||||
| Course Supervisor: | Vinita Cauce | ||||||||
| Study Course Implementer | |||||||||
| Structural Unit: | Statistics Unit | ||||||||
| The Head of Structural Unit: | |||||||||
| Contacts: | 23 Kapselu street, 2nd floor, Riga, +371 67060897, statistika rsu[pnkts]lv, www.rsu.lv/statlab | ||||||||
| Study Course Planning | |||||||||
| Full-Time - Semester No.1 | |||||||||
| Lectures (count) | 0 | Lecture Length (academic hours) | 0 | Total Contact Hours of Lectures | 0 | ||||
| Classes (count) | 8 | Class Length (academic hours) | 4 | Total Contact Hours of Classes | 32 | ||||
| Total Contact Hours | 32 | ||||||||
| Study course description | |||||||||
| Preliminary Knowledge: | Courses Mathematichal Statistics I and II should be successfully acquired before. | ||||||||
| Objective: | Deepen knowledge and strengthen skills in mathematical data processing methods in the IBM SPSS program for the purposes of developing a bachelor's thesis and work in the public health specialty. | ||||||||
| Topic Layout (Full-Time) | |||||||||
| No. | Topic | Type of Implementation | Number | Venue | |||||
| 1 | Data input and exchange with MS Office and IBM SPSS. Data file preparation. Data validation, cleaning (missing values and outliers). | Classes | 2.00 | computer room | |||||
| 2 | Data visualising in tables (IBM SPSS, MS Excel). Interpretation of the results. | Classes | 2.00 | computer room | |||||
| 3 | Data visualising in graphs (IBM SPSS, MS Excel, EpiInfo). Interpretation of the results. | Classes | 2.00 | computer room | |||||
| 4 | Confidence interval calculation (IBM SPSS, MS Excel, EpiInfo, etc.). Interpretation of the results. | Classes | 2.00 | computer room | |||||
| Assessment | |||||||||
| Unaided Work: | Development of a draft of a bachelor's thesis, independent interpretation and description of the obtained results. | ||||||||
| Assessment Criteria: | Active participation in practical classes. Correctly designed thesis draft. Examination, where theses draft will be evaluated: description of the statistical methods of the draft paper, the results part design (10%) and the results of the statistical analysis (chart design (30%), table design (30%) and text design (30%)). | ||||||||
| Final Examination (Full-Time): | Exam | ||||||||
| Final Examination (Part-Time): | |||||||||
| Learning Outcomes | |||||||||
| Knowledge: | Upon successful acquisition of the course, the students will be able to use Excel and IBM SPSS, Word for data processing, analysis, visualisation and formatting. | ||||||||
| Skills: | Upon successful acquisition of the course, the students will be able to: * perform data verification and prepare data for analysis; * filter data accordingly to different criteria; * transform files in IBM SPSS; * construct and edit tables and graphics in IBM SPSS and MS Excel; * correctly report data processing methods in MS Word; * write down activities in IBM SPSS syntax. | ||||||||
| Competencies: | Upon successful acquisition of the course, the students will be able to use Excel and IBM SPSS, Word for data processing, analysis, visualisation and formatting. | ||||||||
| Bibliography | |||||||||
| No. | Reference | ||||||||
| Required Reading | |||||||||
| 1 | Teibe U. Bioloģiskā statistika, LU, 2007. (akceptējams izdevums) | ||||||||
| 2 | Petrie A. & Sabin C. Medical Statistics at a Glance. 2020. | ||||||||
| Additional Reading | |||||||||
| 1 | Jenny V. Freeman, Stephen J. Walters, and Michael J. Campbell. How to Display Data, 2008 | ||||||||
| 2 | Field A. Discovering Statistics using IBM SPSS Statistics. 2018 | ||||||||
