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Methods of Mathematical Statistics in Health Sciences II
Study Course Description
Course Description Statuss:Approved
Course Description Version:3.00
Study Course Accepted:30.04.2024 09:14:10
| Study Course Information | |||||||||
| Course Code: | SL_044 | LQF level: | Level 8 | ||||||
| Credit Points: | 2.00 | ECTS: | 3.00 | ||||||
| Branch of Science: | Mathematics; Theory of Probability and Mathematical Statistics | Target Audience: | Medicine; Pharmacy | ||||||
| Study Course Supervisor | |||||||||
| Course Supervisor: | Māra Grēve | ||||||||
| Study Course Implementer | |||||||||
| Structural Unit: | Statistics Unit | ||||||||
| The Head of Structural Unit: | |||||||||
| Contacts: | 14 Balozu street, Block A, 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) | 4 | Class Length (academic hours) | 4 | Total Contact Hours of Classes | 16 | ||||
| Total Contact Hours | 16 | ||||||||
| Study course description | |||||||||
| Preliminary Knowledge: | Successfully completed course “Methods of Mathematical Statistics in Health Sciences I”. | ||||||||
| Objective: | To provide in-depth knowledge of mostly used statistical methods in health sciences and to offer an insight in proper form for reporting results of statistical analysis. | ||||||||
| Topic Layout (Full-Time) | |||||||||
| No. | Topic | Type of Implementation | Number | Venue | |||||
| 1 | Correlation and association analysis. Insights into regression analysis. Differences between the two methods. | Classes | 1.00 | computer room | |||||
| 2 | Practical tasks. How to navigate statistical tests? Formalization of the research question | Classes | 1.00 | computer room | |||||
| 3 | Introduction to the theory and practice of Analysis of Covariance (ANCOVA and Partial Correlation) | Classes | 1.00 | computer room | |||||
| 4 | Research design development based on data analysis methods. Practical tasks individually and in groups. Working with student data or databases. | Classes | 1.00 | computer room | |||||
| Assessment | |||||||||
| Unaided Work: | 1. Reading literature from the list of Required reading according to topics of lectures and classes. 2. Reviewing examples of statistical analysis results report forms in scientific publications. 3. Recognize the statistical data analysis situations discussed in the classes in one’s own research data. | ||||||||
| Assessment Criteria: | Solved tasks while working individually or in groups (100%). | ||||||||
| Final Examination (Full-Time): | Exam | ||||||||
| Final Examination (Part-Time): | |||||||||
| Learning Outcomes | |||||||||
| Knowledge: | On successful completion of the study course, students will have knowledge that will allow to recognize benefits of various statistical analysis methods and to characterize measurement data using statistical indicators. | ||||||||
| Skills: | On successful completion of the study course, students will be able to combine various statistical methods with the aim to create valid conclusions about data and use suitable reflection tools for statistical analysis in the description of the results. | ||||||||
| Competencies: | On successful completion of the study course, students will be able to justify the choice of statistical methods for data analysis and critically evaluate statistical information given in scientific publications. | ||||||||
| Bibliography | |||||||||
| No. | Reference | ||||||||
| Required Reading | |||||||||
| 1 | Petrie, A., Sabin, C. Medical Statistics at a Glance. 4th edition, Wiley-Blackwell, 2020. | ||||||||
| 2 | Peat, J., Barton, B. Medical Statistics: A Guide to SPSS, Data Analysis and Critical Appraisal. 2nd edition, John Wiley & Sons, 2014. | ||||||||
| 3 | Field, A. Discovering Statistics using IBM SPSS Statistics. Sage Publications, 2018. | ||||||||
| 4 | Torgo, L. Data Mining with R: Learning with Case Studies. 2nd edition. Chapman and Hall/CRC, 2020. | ||||||||
| Additional Reading | |||||||||
| 1 | Mishra, P., Pandey, C. M., Singh, U., Keshri, A., and Sabaretnam, M. 2019. Selection of Appropriate Statistical Methods for Data Analysis. Annals of Cardiac Anaesthesia. 22(3): 297–301. DOI: 10.4103/aca.ACA_248_18 | ||||||||
| 2 | Mishra, P., Pandey, C. M., Singh, U. and Gupta, A. 2018. Scales of Measurement and Presentation of Statistical Data. Ann Card Anaesth. 21(4): 419–422. DOI: 10.4103/aca.ACA_131_18 | ||||||||
| 3 | Spriestersbach, A., Röhrig, B., du Prel, J-B., Gerhold-Ay, A., and Blettner, M. 2009. Descriptive Statistics. The Specification of Statistical Measures and Their Presentation in Tables and Graphs. Part 7 of a Series on Evaluation of Scientific Publications. Dtsch Arztebl Int. 106(36): 578–583. DOI: 10.3238/arztebl.2009.0578 | ||||||||
| 4 | Sperandei, S. 2014. Understanding logistic regression analysis. Biochem Med (Zagreb). 24(1): 12–18. DOI: 10.11613/BM.2014.003 | ||||||||
| 5 | Amrhein, V., Greenland, S., McShane, B. 2019. Scientists rise up against statistical significance. Nature. 567(7748):305-307. DOI: 10.1038/d41586-019-00857-9 | ||||||||
| 6 | Zwiener, I., Blettner, M. and Hommel, G. 2011. Survival Analysis. Part 15 of a Series on Evaluation of Scientific Publications. Dtsch Arztebl Int. 108(10): 163–169. DOI: 10.3238/arztebl.2011.0163 | ||||||||
| Other Information Sources | |||||||||
| 1 | Laerd statistics. Available from: https://statistics.laerd.com/ | ||||||||
| 2 | Praktiskā biometrija. Pieejams no: https://bookdown.org/delferts/PBB_gramata/ | ||||||||
| 3 | Statistics How To. Available from: https://www.statisticshowto.com/probability-and-statistics/… | ||||||||
| 4 | Ārvalstu studentiem/For International students | ||||||||
| 5 | Laerd statistics. Available from: https://statistics.laerd.com/ | ||||||||
| 6 | Statistics How To. Available from: https://www.statisticshowto.com/probability-and-statistics/… | ||||||||
