Veidlapa Nr. M-3 (8)
Study Course Description
Health Statistics
Course Code
SL_021
Branch of Science
Mathematics; Theory of probability and mathematical statistics
ECTS
3.00
Target Audience
Communication Science
LQF
Level 7
Study Type And Form
Full-Time
Study Course Implementer
Course Supervisor
Diāna Kalniņa
Structure Unit Manager
Andrejs Ivanovs
Structural Unit
Statistics Unit
Contacts
Baložu iela 14, Block A, Riga, statistika@rsu.lv, +371 67060897
About Study Course
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.
Preliminary Knowledge
Basic knowledge of Mathematics.
Learning Outcomes
Knowledge
1.1. Accurate use of basic statistical concepts. 2. Describe measurement data using basic statistical tests and indicators.
Skills
1.1. 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.
Competences
1.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.
Assessment
Individual work
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Title
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% from total grade
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Grade
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|---|---|---|
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1.
Individual work |
-
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-
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Students study literature and e-study materials outside classes and lectures.
Analysis of scientific publications to raise awareness of the study course.
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Examination
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Title
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% from total grade
|
Grade
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|---|---|---|
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1.
Examination |
-
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-
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|
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.
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Study Course Theme Plan
FULL-TIME
Part 1
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Lecture
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Modality
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Location
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Contact hours
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|---|---|---|
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On site
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Computer room
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2
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Topics
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Introduction to statistics. The role of statistics in the research process. General population and sample. Sample size and structure. Data types. The scales.
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-
Lecture
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Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Introduction to statistics. The role of statistics in the research process. General population and sample. Sample size and structure. Data types. The scales.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
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2
|
Topics
|
Introduction to the statistical data processing program IBM SPSS. Basic operations with data in IBM SPSS.
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-
Class/Seminar
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Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Introduction to the statistical data processing program IBM SPSS. Basic operations with data in IBM SPSS.
|
-
Lecture
|
Modality
|
Location
|
Contact hours
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|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
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Descriptive statistics for qualitative and quantitative data. Central tendency, distribution and representation indicators. Confidence interval.
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-
Class/Seminar
|
Modality
|
Location
|
Contact hours
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|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Descriptive statistics indicators IBM SPSS. Normal distribution and its characteristic descriptive statistics.
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-
Lecture
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Modality
|
Location
|
Contact hours
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|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Statistical hypotheses. Possible errors in hypothesis test. P-value.
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-
Lecture
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Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
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Dependent and independent selections. T-tests.
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-
Class/Seminar
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Modality
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Location
|
Contact hours
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|---|---|---|
|
On site
|
Computer room
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2
|
Topics
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Parametric data processing methods for quantitative data using IBM SPSS.
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-
Lecture
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Modality
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Location
|
Contact hours
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|---|---|---|
|
On site
|
Computer room
|
2
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Topics
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Publication and presentation of research results.
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-
Lecture
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Modality
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Location
|
Contact hours
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|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
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Correlations analysis. Regression analysis.
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-
Class/Seminar
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Modality
|
Location
|
Contact hours
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|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Correlations analysis. Regression analysis.
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-
Class/Seminar
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Modality
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Location
|
Contact hours
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|---|---|---|
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On site
|
Computer room
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2
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Topics
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Non-Parametric data processing methods for quantitative data using IBM SPSS.
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-
Class/Seminar
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Modality
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Location
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Contact hours
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|---|---|---|
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On site
|
Computer room
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2
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Topics
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Seminar "Analysis of publications".
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-
Class/Seminar
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Modality
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Location
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Contact hours
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|---|---|---|
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On site
|
Computer room
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2
|
Topics
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Final independent work.
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-
Class/Seminar
|
Modality
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Location
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Contact hours
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|---|---|---|
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On site
|
Computer room
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2
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Topics
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Final independent work.
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Total ECTS (Creditpoints):
3.00
Contact hours:
32 Academic Hours
Final Examination:
Exam (Written)
Bibliography
Required Reading
1.
K. Mārtinsone, A. Pipere, D. Kamerāde. Pētniecība: Teorija un prakse. Izdevniecība RaKa, 2016
2.
Statistika. /Krastiņš O., Ciemiņa I./ Rīga: LR CSP, 2003. - 267 lpp.
3.
OpenIntro Statistics. 3rd ed, 2015, 436 lpp
Additional Reading
1.
Varbūtību teorija un matemātiskā statistika /Vasermanis E., Šķiltere D./ Rīga, 2003. -186 lpp.
2.
SPSS statistics for social scientists /Acton, C., et al./ Basingstoke: Palgrave Macmillan, 2009. 363 lpp.
3.
Leavy. 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
1.
Choosing the Correct Statistic in SAS, STATA, SPSS and R
2.
Latvijas statistikas gadagrāmata, 2017. Rīga: Centrālā statistikas pārvalde, 2018., 550 lpp
3.
LR CSP mājas lapa