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Health Statistics

Study Course Description

Course Description Statuss:Approved
Course Description Version:8.00
Study Course Accepted:17.06.2022 15:43:39
Study Course Information
Course Code:SL_021LQF level:Level 7
Credit Points:2.00ECTS:3.00
Branch of Science:Mathematics; Theory of Probability and Mathematical StatisticsTarget Audience:Communication Science
Study Course Supervisor
Course Supervisor:Diāna Kalniņa
Study Course Implementer
Structural Unit:Statistics Unit
The Head of Structural Unit:
Contacts:Baložu iela 14, Block A, Riga, statistikaatrsu[pnkts]lv, +371 67060897
Study Course Planning
Full-Time - Semester No.1
Lectures (count)7Lecture Length (academic hours)2Total Contact Hours of Lectures14
Classes (count)9Class Length (academic hours)2Total Contact Hours of Classes18
Total Contact Hours32
Study course description
Preliminary Knowledge:
Basic knowledge of Mathematics.
Objective:
Promote knowledge acquisition of key issues, statistical indicators and tests used in health statistics. Raise the students’ awareness of the role of statistics in research and interpretation.
Topic Layout (Full-Time)
No.TopicType of ImplementationNumberVenue
1Introduction to statistics. The role of statistics in the research process. General population and sample. Sample size and structure. Data types. The scales.Lectures2.00computer room
2Introduction to the statistical data processing program IBM SPSS. Basic operations with data in IBM SPSS.Classes2.00computer room
3Descriptive statistics for qualitative and quantitative data. Central tendency, distribution and representation indicators. Confidence interval.Lectures1.00computer room
4Descriptive statistics indicators IBM SPSS. Normal distribution and its characteristic descriptive statistics.Classes1.00computer room
5Statistical hypotheses. Possible errors in hypothesis test. P-value.Lectures1.00computer room
6Dependent and independent selections. T-tests.Lectures1.00computer room
7Parametric data processing methods for quantitative data using IBM SPSS.Classes1.00computer room
8Publication and presentation of research results.Lectures1.00computer room
9Correlations analysis. Regression analysis.Lectures1.00computer room
Classes1.00computer room
10Non-Parametric data processing methods for quantitative data using IBM SPSS.Classes1.00computer room
11Seminar "Analysis of publications".Classes1.00computer room
12Final independent work.Classes2.00computer room
Assessment
Unaided Work:
Students study literature and e-study materials outside classes and lectures. Analysis of scientific publications to raise awareness of the study course.
Assessment Criteria:
At the end of the course, students independently do their practical work. The course is successfully completed, if the assessment of the practical work is at least 5 points.
Final Examination (Full-Time):Exam (Written)
Final Examination (Part-Time):
Learning Outcomes
Knowledge:1. Accurate use of basic statistical concepts. 2. Describe measurement data using basic statistical tests and indicators.
Skills:1. Able to enter data in the processing program. 2. Determine the type of data and evaluate their distribution. 3. Able to formulate hypotheses (zero; alternative) and choose the appropriate test. 4. Able to calculate ratios of the regression equation. 5. Able to calculate Pearson and Spearman’s correlation ratios. 6. Able to draw data specific diagrams.
Competencies:Students will be able to select appropriate statistical data processing methods, formulate hypotheses, process data and interpret the obtained results. Evaluate the obtained data using statistical and analytical tools.
Bibliography
No.Reference
Required Reading
1K. Mārtinsone, A. Pipere, D. Kamerāde. Pētniecība: Teorija un prakse. Izdevniecība RaKa, 2016
2Statistika. /Krastiņš O., Ciemiņa I./ Rīga: LR CSP, 2003. - 267 lpp.
3OpenIntro Statistics. 3rd ed, 2015, 436 lpp
Additional Reading
1Varbūtību teorija un matemātiskā statistika /Vasermanis E., Šķiltere D./ Rīga, 2003. -186 lpp.
2SPSS statistics for social scientists /Acton, C., et al./ Basingstoke: Palgrave Macmillan, 2009. 363 lpp.
3Leavy. P. (ed). The Oxford Handbook of Qualitative Research. New York: Oxford University Press, 2014
4 Бююль А., Цефель П. SPSS: искусство обработки информации. Анализ статистических данных и восстановление скрытых закономерностей: Пер. с нем. СПб.: ООО«DiaSoftЮП», 2005
Other Information Sources
1Choosing the Correct Statistic in SAS, STATA, SPSS and R
2Latvijas statistikas gadagrāmata, 2017. Rīga: Centrālā statistikas pārvalde, 2018., 550 lpp
3LR CSP mājas lapa