Veidlapa Nr. M-3 (8)
Study Course Description
Basic Statistics
Course Code
LF_620
Branch of Science
Mathematics; Theory of probability and mathematical statistics
ECTS
3.00
Target Audience
Nursing Science
LQF
Level 6
Study Type And Form
Full-Time
Study Course Implementer
Course Supervisor
Arvils Roga
Structure Unit Manager
Dita Role
Structural Unit
RSU Liepāja Branch
Contacts
23 Kapselu street, 2nd floor, Riga, +371 67060897, statistika@rsu.lv, www.rsu.lv/statlab
About Study Course
Objective
To get basic knowledge in data processing methods (descriptive statistics, inferential statistics to estimate differences), that can be used in thesis work and in chosen specialty.
Preliminary Knowledge
Secondary school knowledge in mathematics and informatics.
Learning Outcomes
Knowledge
1.After completion of this course, students will demonstrate basic knowledge that allows to: * recognise terminology used in statistics and basic methods used in different publications; * know IBM SPSS offered data processing tools; * know data processing method criterias; * correctly interpret the most important statistical indicators.
Skills
1.After completion of this course, students will demonstrate skills: * to input and edit data in computer programs MS Excel and IBM SPSS; * to prepare data for statistical analysis correctly; * to choose appropriate data processing methods, incl., will be able to do statistical hypothesis testing; * statistically analyse research data using IBM SPSS program; * create tables and graphs in IBM SPSS program with obtained results; * precisely describe obtained research results.
Competences
1.After completion of this course, students will be able to argument and make decisions about statistical data processing methods, use them to achieve research aims, using IBM SPSS, practically use learned statistical basic methods to process research data.
Assessment
Individual work
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Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Individual work |
-
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-
|
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1. Individual work with the literature – prepare to lectures according to plan. 2. Individual analysis of scientific publication, that has to be presented in the last lecture. 3. Individual work – each student will receive a research data file (or student can use their own) with previously defined research tasks. Student will statistically process data to reach defined tasks using descriptive statistics, inferential statistics and/or analytical statistics methods. As well as to present obtained results in the last lecture, using defined formatting style.
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Examination
|
Title
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% from total grade
|
Grade
|
|---|---|---|
|
1.
Examination |
-
|
-
|
|
Participation in practical lectures. For every missed lecture – practical tasks and control questions about missed topic. After completion of this course: Multiple choice test with theoretical questions in statistics.
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Study Course Theme Plan
FULL-TIME
Part 1
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
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|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Introduction to statistics, the role of statistics in research process. Types of data.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Preparation of data for database. Introduction to IBM SPSS. Basic operations with data in IBM SPSS.
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-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Descriptive statistics in IBM SPSS.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Descriptive statistics of the Normal distribution.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Creation of tables and diagrams in IBM SPSS according to data type.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Statistical hypothesis, types of statistical hypothesis. Hypothesis testing. P value. Confidence intervals.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Parametric statistics for quantitative data for 2 independent or paired samples.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Nonparametric statistics for quantitative or ordinal data for 2 independent or paired samples.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Parametric and nonparametric data processing methods for 3 or more independent or paired samples.
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-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Qualitative data processing for independent and dependent samples. Odds ratio, relative risk.
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-
Class/Seminar
|
Modality
|
Location
|
Contact hours
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|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Reliability analysis. (Cronbach's alpha).
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-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Practical work with data in IBM SPSS.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Practical work with data in IBM SPSS.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Analysis of scientific publications.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Independent work with data using IBM SPSS.
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Student presentations.
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Total ECTS (Creditpoints):
3.00
Contact hours:
32 Academic Hours
Final Examination:
Exam (Written)
Bibliography
Required Reading
1.
Teibe U. Bioloģiskā statistika. Rīga: LU 2007 - 156 lpp.
2.
Petrie A. & Sabin C. Medical Statistics at a Glance, 3rd edition, 2009. ISBN: 978-1-405-18051-1
3.
Field A. Discovering Statistics using IBM SPSS Statistics, 4th edition, ISBN-13: 978-1446249185, 2013.