.
Applied Biostatistics
Study Course Description
Course Description Statuss:Approved
Course Description Version:4.00
Study Course Accepted:21.08.2023 11:18:52
| Study Course Information | |||||||||
| Course Code: | SL_033 | LQF level: | All Levels | ||||||
| Credit Points: | 2.00 | ECTS: | 3.00 | ||||||
| Branch of Science: | Mathematics; Theory of Probability and Mathematical Statistics | Target Audience: | Pharmacy; Public Health; Medicine; Dentistry | ||||||
| Study Course Supervisor | |||||||||
| Course Supervisor: | Māris Munkevics | ||||||||
| 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) | 8 | Class Length (academic hours) | 4 | Total Contact Hours of Classes | 32 | ||||
| Total Contact Hours | 32 | ||||||||
| Study course description | |||||||||
| Preliminary Knowledge: | Basic knowledge in data analysis. Acquired, for example, in course SL_001 "Biostatistics" or its equivalents. | ||||||||
| Objective: | To introduce students with open access data analysis tool R and get acquainted with the possibilities in solving data analysis violations. The most commonly used data analysis methods have strong prerequisites that often are violated due to lack of expertise in addressing them. It is planned to introduce students with tools and methods to reduce data analysis violations. | ||||||||
| Topic Layout (Full-Time) | |||||||||
| No. | Topic | Type of Implementation | Number | Venue | |||||
| 1 | Introduction to R and RStudio. | Classes | 1.00 | computer room | |||||
| 2 | R graphics. | Classes | 1.00 | computer room | |||||
| 3 | Quantitative data analysis. | Classes | 1.00 | computer room | |||||
| 4 | Correlations and simple regressions. | Classes | 1.00 | computer room | |||||
| 5 | Multivariate analysis. | Classes | 1.00 | computer room | |||||
| 6 | Correlation and variance structures. | Classes | 1.00 | computer room | |||||
| 7 | Mixed effects. | Classes | 1.00 | computer room | |||||
| 8 | Meta-analysis. | Classes | 1.00 | computer room | |||||
| Assessment | |||||||||
| Unaided Work: | Every class will contain independent work – student individually prepares for them. Task solutions electronically submitable for evaluation. In order to evaluate the quality of the study course as a whole, the student must fill out the study course evaluation questionnaire on the Student Portal. | ||||||||
| Assessment Criteria: | Submitted tasks will be graded and cumulatively form 50% of the final grade. Remaining 50% will be formed by grade in the final test. | ||||||||
| Final Examination (Full-Time): | Exam (Written) | ||||||||
| Final Examination (Part-Time): | |||||||||
| Learning Outcomes | |||||||||
| Knowledge: | Students will receive knowledge in programming in open access data analysis software and options in dealing with most common violations during data anlysis. | ||||||||
| Skills: | Students will be practically dealing with most common violations during data anlysis. | ||||||||
| Competencies: | Frequently used data analysis methods have strong prerequisites that are often violated. The course participants will have the competence to address these violations analytically. | ||||||||
| Bibliography | |||||||||
| No. | Reference | ||||||||
| Required Reading | |||||||||
| 1 | Sokal, R.R. & Rohlf, F.J. 2009. Introduction to Biostatistics. 2nd edition. | ||||||||
| 2 | Dalgaard, P. 2008. Introductory Statistics with R. 2nd edition. | ||||||||
| 3 | Field, A., Miles, J., Field, Z. 2012. Discovering statistics using R. | ||||||||
| Additional Reading | |||||||||
| 1 | Demidenko, E. 2013. Mixed models: theory and applications with R. 2nd edition | ||||||||
| 2 | Zuur, A., Ieno, E.N., Walker, N.J., Saveliev, A.A., Smith, G.M. 2009. Mixed Effects Models and Extensions in Ecology with R. | ||||||||
| Other Information Sources | |||||||||
| 1 | Elferts D., Praktiskā biometrija, 2016, elektroniskā grāmata. | ||||||||
