Veidlapa Nr. M-3 (8)
Study Course Description
Data Processing and Analysis in Microsoft Excel
Course Code
SL_032
Branch of Science
Mathematics; Theory of probability and mathematical statistics
ECTS
1.50
Target Audience
Communication Science; Dentistry; Medicine; Nursing Science; Pharmacy; Political Science; Psychology; Public Health; Rehabilitation
LQF
All Levels
Study Type And Form
Full-Time
Study Course Implementer
Course Supervisor
Dina Barute
Structure Unit Manager
Andrejs Ivanovs
Structural Unit
Statistics Unit
Contacts
14 Baložu street, Riga, +371 67060897, statistika@rsu.lv, www.rsu.lv/en/statistics-unit
About Study Course
Objective
To get acquainted with the capabilities of MS Excel for data processing, display, and analysis. Graduates of the course will acquire the basic skills and knowledge that will allow them to master more complex techniques individually.
Preliminary Knowledge
Secondary school background in mathematics and informatics.
Learning Outcomes
Knowledge
1.After completion of this course, the student will demonstrate basic knowledge that allows: * to recognise terminology used in statistics and basic methods used in different publications; * to know MS Excel offered data processing tools; * to know data processing method criterias; * to correctly interpet the most important statistical indicators.
Skills
1.After completion of this course, the student will demonstrate skills: * to input and edit data in computer program MS Excel; * to prepare data for statistical analysis correctly; * to choose appropriate data provessing methods, incl., are able to do statistical hypothesis testing; * to statistically analyse research data using computer program MS Excel; * to create tables and graphs in MS Excel programme with obtained results; * to describe obtained research results correctly.
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 computer program MS Excel, practically use learned statistical basic methods to process research data.
Assessment
Individual work
|
Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Individual work |
-
|
-
|
|
In each class students have exercises, independent work; literary studies.
In order to evaluate the quality of the study course as a whole, the student must fill out the study course evaluation questionnaire on the Student Portal.
|
||
Examination
|
Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Examination |
-
|
-
|
|
At the end of the course students will have a practical work. This course will be passed, if grade of practical work will be at least 5.
|
||
Study Course Theme Plan
FULL-TIME
Part 1
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Excel basics
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Formulas in Excel
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Descriptive statistics with Excel
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Plots and diagrams
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Pivot tables
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Parametric tests
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Comparing proportions
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Computer room
|
2
|
Topics
|
Correlation and linear regression
|
Total ECTS (Creditpoints):
1.50
Contact hours:
16 Academic Hours
Final Examination:
Test
Bibliography
Required Reading
1.
Verschuuren, G. M. N. Excel 2007 for Scientists and Engineers. 2nd ed., rev. and expanded. Uniontown, OH : Holy Macro! Books. 2008
Additional Reading
1.
Collie, R. and Singh, A. Power Pivot and Power BI: The Excel User's Guide to DAX, Power Query, Power BI & Power Pivot in Excel 2010-2016, Holy Macro! Books. 2016
2.
Winston, W. Microsoft Excel 2013 Data Analysis and Business Modeling, Microsoft Corporation, O’Reilly Media, Inc 2014