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Mathematical Statistics II
Study Course Description
Course Description Statuss:Approved
Course Description Version:6.00
Study Course Accepted:12.08.2022 11:06:49
Study Course Information | |||||||||
Course Code: | SL_009 | 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, statistikarsu[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: | Course Mathematichal Statistics I should be taken before. | ||||||||
Objective: | Enhance knowledge and practical skills about data analyse basic methods in SPSS, strengthen those skills with programmes like Epilinfo, etc. | ||||||||
Topic Layout (Full-Time) | |||||||||
No. | Topic | Type of Implementation | Number | Venue | |||||
1 | Introduction. Measuring association in 2 x 2 contingency table. Measuring effect size in contigency table analysis. | Classes | 1.00 | computer room | |||||
2 | Estimating the incidence, mortality and prevelence or disease. Standartization. | Classes | 1.00 | computer room | |||||
3 | Correlation. Lienear regression. | Classes | 1.00 | computer room | |||||
4 | Program EpiInfo. | Classes | 2.00 | computer room | |||||
5 | Other statistical programmes, calculators. | Classes | 1.00 | computer room | |||||
6 | Course summary. Individual work with data. | Classes | 1.00 | computer room | |||||
7 | Individual work presentation. | Classes | 1.00 | computer room | |||||
Assessment | |||||||||
Unaided Work: | Individual work with literature, in EpiInfo program – prepare for lectures, unknown terminology should be found out, home tasks should be done. | ||||||||
Assessment Criteria: | Active participation in practical lectures. Individual work about advanced descriptive statistic and hypothesis testing, make calculations and interpet results. For every missed lecture – a summary should be prepared (at least one paper, size A4). At the end of the study course, written examination: computerised testing (30 questions) on representative names and decision-making in data processing – 50%, practical resolution – 30%, independent work- 20%. | ||||||||
Final Examination (Full-Time): | Exam (Written) | ||||||||
Final Examination (Part-Time): | |||||||||
Learning Outcomes | |||||||||
Knowledge: | Upon successful acquisition of the course, the students will know: * about statistical calculations in different programmes; * about correlation and regression analysis. | ||||||||
Skills: | Upon successful acquisition of the course, the students will be able to: * do hypothesis testing with one or multiple samples; * interpret quantitative variable correlation; * calculate descriptive statistics estimators; make graphs un do hypothesis testing in MS Excel, SPSS, EpiInfo programmes, and use online statistical calculators; * interpret data processing results accordingly to their speciality. | ||||||||
Competencies: | As a result of successful training, students will be able to make practical use of computer programs and calculators in the study process and in the professional sphere for data processing. | ||||||||
Bibliography | |||||||||
No. | Reference | ||||||||
Required Reading | |||||||||
1 | Teibe U. Bioloģiskā statistika, LU, 2007. SL_009 | ||||||||
2 | Field A. Discovering Statistics using IBM SPSS Statistics. 5th edition, 2018. | ||||||||
3 | Petrie A. & Sabin C. Medical Statistics at a Glance. 2020 |