Veidlapa Nr. M-3 (8)
Study Course Description
Basic Statistics in Nursing
Course Code
LF_679
Branch of Science
Clinical medicine
ECTS
3.00
Target Audience
Nursing Science
LQF
Level 6
Study Type And Form
Full-Time
Study Course Implementer
Course Supervisor
Dina Barute
Structure Unit Manager
Dita Role
Structural Unit
RSU Liepāja Branch
Contacts
-
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 Microsoft Excel and IBM SPSS offered data processing tools; * know data processing method criteria; * 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 – Microsoft 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 Microsoft Excel and 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
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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 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
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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.
Examination |
-
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-
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Participation in practical lectures. For every missed lecture – practical tasks and control questions about missed topic. On completion of this course – an exam: 1. Oral presentation of publication analysis and independent work (50%). 2. Exam – test with multiple choice questions in statistics (50%).
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Study Course Theme Plan
FULL-TIME
Part 1
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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
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Auditorium
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2
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Topics
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Introduction to statistics, the role of statistics in research process. Types of data.
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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
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Auditorium
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2
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Topics
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Preparation of data for database. Introduction to IBM SPSS. Basic operations with data in Microsoft Excel and 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
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Auditorium
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2
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Topics
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Descriptive statistics in Microsoft Excel and 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
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Auditorium
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2
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Topics
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Descriptive statistics of the Normal distribution.
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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
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Auditorium
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2
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Topics
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Creation of tables and diagrams in Microsoft Excel and IBM SPSS according to data type.
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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
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Auditorium
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2
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Topics
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Statistical hypothesis, types of statistical hypothesis. Hypothesis testing. P value. Confidence intervals.
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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
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Auditorium
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2
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Topics
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Parametric and nonparametric statistics for quantitative and ordinal data for 2 or more independent or paired samples.
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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
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Auditorium
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2
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Topics
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Parametric and nonparametric statistics for quantitative and ordinal data for 2 or more independent or paired samples.
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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
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Auditorium
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2
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Topics
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Parametric and nonparametric statistics for quantitative and ordinal data for 2 or more independent or paired samples.
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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
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Auditorium
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2
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Topics
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Qualitative data processing for independent and dependent samples. Odds ratio, relative risk.
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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
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Auditorium
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2
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Topics
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Correlation and Linear regression.
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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
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Auditorium
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2
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Topics
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Correlation and Linear regression.
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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
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Auditorium
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2
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Topics
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Practical work with data in 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
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Auditorium
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2
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Topics
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Analysis of publication.
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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
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Auditorium
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2
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Topics
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Independent work with 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
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Auditorium
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2
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Topics
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Students presentations.
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Total ECTS (Creditpoints):
3.00
Contact hours:
32 Academic Hours
Final Examination:
Exam
Bibliography
Required Reading
1.
Petrie A. & Sabin C. Medical Statistics at a Glance, 3rd edition, 2009. ISBN: 978-1-405-18051-1
2.
Field A. Discovering Statistics using IBM SPSS Statistics, 4th edition, ISBN-13: 978-1446249185, 2013.
3.
Teibe U. Bioloģiskā statistika. Rīga: LU 2007 - 156 lpp.