.
Basics of Biostatistics
Study Course Description
Course Description Statuss:Approved
Course Description Version:7.00
Study Course Accepted:26.01.2022 11:16:22
| Study Course Information | |||||||||
| Course Code: | SL_002 | LQF level: | Level 7 | ||||||
| Credit Points: | 2.00 | ECTS: | 3.00 | ||||||
| Branch of Science: | Mathematics; Theory of Probability and Mathematical Statistics | Target Audience: | Medicine | ||||||
| Study Course Supervisor | |||||||||
| Course Supervisor: | Ieva Reine | ||||||||
| Study Course Implementer | |||||||||
| Structural Unit: | Statistics Unit | ||||||||
| The Head of Structural Unit: | |||||||||
| Contacts: | 23 Kapselu street, 2nd floor, Riga, statistika rsu[pnkts]lv, +371 67060897 | ||||||||
| Study Course Planning | |||||||||
| Full-Time - Semester No.1 | |||||||||
| Lectures (count) | 0 | Lecture Length (academic hours) | 0 | Total Contact Hours of Lectures | 0 | ||||
| Classes (count) | 4 | Class Length (academic hours) | 2 | Total Contact Hours of Classes | 8 | ||||
| Total Contact Hours | 8 | ||||||||
| Full-Time - Semester No.2 | |||||||||
| Lectures (count) | 0 | Lecture Length (academic hours) | 0 | Total Contact Hours of Lectures | 0 | ||||
| Classes (count) | 6 | Class Length (academic hours) | 4 | Total Contact Hours of Classes | 24 | ||||
| Total Contact Hours | 24 | ||||||||
| Study course description | |||||||||
| Preliminary Knowledge: | Secondary school level knowledge in Mathematics and Informatics. | ||||||||
| Objective: | To provide basic knowledge and skills in the planning of appropriate quantitative research, data mining and statistical data processing methods (descriptive statistics and inference statistics methods for the assessment of differences) necessary for the development of scientific research work and application of statistical indicators in their speciality. | ||||||||
| Topic Layout (Full-Time) | |||||||||
| No. | Topic | Type of Implementation | Number | Venue | |||||
| 1 | The role of statistics in the research process, an introduction to qualitative and quantitative research, data acquisition and analysis, descriptive statistics and methods of lock statistics; research methods in medical science, data mining methods: primary and secondary. | Classes | 1.00 | computer room | |||||
| 2 | Data collection: surveys, interviews, and document reviews – methods, advantages and disadvantages. | Classes | 1.00 | computer room | |||||
| 3 | Research objectives and methodology selection. Components of a scientific project. | Classes | 1.00 | computer room | |||||
| 4 | Research metdods in medical science, integrity of data mining, scientific credibility, quality criteria. | Classes | 1.00 | computer room | |||||
| 5 | Sampling in primary data acquisition. Sampling errors. Analysis of non-parametric samples for quantitative data. | Classes | 1.00 | computer room | |||||
| 6 | Data systematisation – descriptive statistics. Qualitative and quantitative variables. Statistical indicators. | Classes | 1.00 | computer room | |||||
| 7 | Presentation of statistical data. Preparation and presentation of tables and charts, descriptive statistics, calculation of sample size. | Classes | 1.00 | computer room | |||||
| 8 | Data distribution, statistical hypotheses, statistical significance, types of distribution testing. | Classes | 1.00 | computer room | |||||
| 9 | Variation indicators, probability theory. | Classes | 1.00 | computer room | |||||
| 10 | Presentation of practical work, exam. | Classes | 1.00 | computer room | |||||
| Assessment | |||||||||
| Unaided Work: | 1. Individual work with the literature – prepare to lectures accordingly to the plan. 2. Individual data analysis. | ||||||||
| Assessment Criteria: | Participation in practical lectures – individual work and active participation during the sessions. The practical application of the acquired statistical terms and methods – practical work (data analysis and interpretation of the results) at the end of the course (50 percent). On completion of this course – a multiple choice test with 25 theoretical questions in statistics (50 percent). Passed examination above 60 percent of both tasks together. | ||||||||
| Final Examination (Full-Time): | Exam (Written) | ||||||||
| Final Examination (Part-Time): | |||||||||
| Learning Outcomes | |||||||||
| Knowledge: | The aim of the course is to provide basic knowledge and skills in the planning of appropriate quantitative research, data mining, statistical data processing methods (descriptive statistics and inference statistics methods for the assessment of differences) necessary for the development of scientific research work and application of statistical indicators in their specialty. After completing the course, the students will have acquired the knowledge that will allow to: * choose the most appropriate data collection method; * recognise statistical terminology and basic methods used in various types of publications; * manually implement commonly used data analysis methods; * know the criteria for using data processing techniques; * correctly interpret the most important statistical indicators. | ||||||||
| Skills: | As a result of study course acquisition students will be able to: * choose appropriate data processing methods, including ability to perform statistical hypotheses testing; * statistically process research data; * correctly prepare data for statistical processing; * create tables and charts with the obtained results. | ||||||||
| Competencies: | Upon completion of this course, students will be able to argument and make decisions about statistical data processing methods, use them to achieve research aims. | ||||||||
| Bibliography | |||||||||
| No. | Reference | ||||||||
| Required Reading | |||||||||
| 1 | Sokal, R. R., Rohlf, F. J. J. Biometry: the principles and practice of statistics in biological research. 3rd edition. W.H. Freeman and Company, 2012 (akceptējams izdevums) | ||||||||
| 2 | Blettner, M., Heuer, C., Razum, O. Critical reading of epidemiological papers. A guide. Eur J Public Health. 2001;11:97–101. (akceptējams izdevums) | ||||||||
| 3 | Röhrig, B., du Prel, Jean-Baptist, Wachtlin, D., Blettner, M. Types of Study in Medical Research. Dtsch Arztebl Int. 2009 Apr; 106(15): 262–268. (akceptējams izdevums) | ||||||||
| 4 | Teibe, U. Bioloģiskā statistika. Rīga: LU Akadēmiskais apgāds, 2007, p 155. (akceptējams izdevums) | ||||||||
| 5 | Ārvalstu studentiem/For International students: | ||||||||
| 6 | Sokal, R. R., Rohlf, F. J. J. Biometry: the principles and practice of statistics in biological research. 3rd edition. W.H. Freeman and Company, 2012 (akceptējams izdevums) | ||||||||
| 7 | Blettner, M., Heuer, C., Razum, O. Critical reading of epidemiological papers. A guide. Eur J Public Health. 2001;11:97–101. (akceptējams izdevums) | ||||||||
| Additional Reading | |||||||||
| 1 | Campbell, M. J., Machin, D. Medical Statistics: A Textbook for the Health Sciences. 5th edition. John Wiley & Sons, 2021. | ||||||||
| Other Information Sources | |||||||||
| 1 | Orlovska, A. Statistika: mācību grāmata. RTU izdevniecība, 2012, p 191. | ||||||||
| 2 | Dalgaard, P. Introductory Statistics with R. 2nd edition. Springer, New York, 2008. doi:10.1007/978-0-387-79054-1 | ||||||||
| 3 | Ārvalstu studentiem/For International students: | ||||||||
| 4 | Dalgaard, P. Introductory Statistics with R. 2nd edition. Springer, New York, 2008. doi:10.1007/978-0-387-79054-1 | ||||||||
