Veidlapa Nr. M-3 (8)
Study Course Description
Basic Statistics
Course Code
SL_018
Branch of Science
Mathematics; Theory of probability and mathematical statistics
ECTS
3.00
Target Audience
Nursing Science
LQF
Level 7
Study Type And Form
Full-Time
Study Course Implementer
Course Supervisor
Madara Miķelsone
Structure Unit Manager
Andrejs Ivanovs
Structural Unit
Statistics Unit
Contacts
14 Balozu street, Block A, Riga, +371 67060897, statistika@rsu.lv, www.rsu.lv/statlab
About Study Course
Objective
Provide basic information about the structure of statistical methods, work with IBM SPSS, data visualization and to recognize statistical methods which are used in medical publications.
Preliminary Knowledge
Students need background knowledge in mathematics at least at secondary level and basic computer skills.
Learning Outcomes
Knowledge
1.After completion of this course, students will demonstrate basic knowledge that allow: * To visualize statistical data correctly; * Create an online questionnaire.
Skills
1.After completion of this course, students will be able to: * demonstrate the knowledge required for correct input of research data in MS Excel and IBM SPSS; * combine the theory and methods necessary for summarizing and visualizing the research results; * navigate the principles of creating a database; * perform research work related to the basic manipulations of descriptive statistics in IBM SPSS.
Competences
1.Skills to identify and apply the most important basic concepts and terminology in practice.
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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1. Individual work with literature – accordingly topics. 2. Each student will be provided with a research data file (or they can use their own research data) with defined research objectives - to statistically process the data in order to achieve the defined objectives, using descriptive statistics, incl. data visualization and report the results in the final class.
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Examination
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Title
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% from total grade
|
Grade
|
|---|---|---|
|
1.
Examination |
-
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-
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Practical seminar attendance (50%).
For every missed lecture a practical assingment.
After completion of study course exam – presentation of individual work (50%).
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Study Course Theme Plan
FULL-TIME
Part 1
-
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
|
Auditorium
|
2
|
Topics
|
Introduction. The importance of statistics for health care professionals. The use of statistical methods in medical publications.
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-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Auditorium
|
2
|
Topics
|
Introduction. The importance of statistics for health care professionals. The use of statistical methods in medical publications.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Introduction to IBM SPSS. Import and export of data. Basic work with IBM SPSS.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Introduction to IBM SPSS. Import and export of data. Basic work with IBM SPSS.
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Auditorium
|
2
|
Topics
|
Descriptive statistics for qualitative and quantitative data.
|
-
Lecture
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Modality
|
Location
|
Contact hours
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|---|---|---|
|
On site
|
Auditorium
|
2
|
Topics
|
Qualitative and quantitative analysis methods based on mathematical statistics.
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-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Data visualization in IBM SPSS.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Data visualization in IBM SPSS.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Auditorium
|
2
|
Topics
|
Work with Microsoft Excel for data processing and visualizations.
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-
Lecture
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Modality
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Location
|
Contact hours
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|---|---|---|
|
On site
|
Auditorium
|
2
|
Topics
|
Introduction to database creation for internet surveys.
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-
Class/Seminar
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Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Independent work with data analysis and visualization of research data.
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Presentation of independent work.
|
Total ECTS (Creditpoints):
3.00
Contact hours:
24 Academic Hours
Final Examination:
Exam (Written)
Bibliography
Required Reading
1.
Petrie A. & Sabin C. Medical Statistics at a Glance. 4th edition, 2020.
2.
Field A. Discovering Statistics using IBM SPSS Statistics. 4th edition, 2018.