Data Processing and Analysis in Microsoft Excel
Study Course Implementer
14 Baložu street, Riga, +371 67060897, statistika@rsu.lv, www.rsu.lv/en/statistics-unit
About Study Course
Objective
Preliminary Knowledge
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
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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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In each class students have exercises, independent work; literary studies. Students will statistically process data to reach defined tasks using descriptive statistics and inferential statistics methods.
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.
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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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For successful integration of knowledge and to prepare for the final exam, the student performs the following activities (mandatory, not graded): 1. Participation in practical lectures. A practical assignment for each missed class. 2. Oral presentation of independent work. After completion of this course – exam. The grade of the course is cumulative, where: 50% – test with practical tasks using datasets, 50% – exam (multiple-choice test with theoretical and practical questions in statistics).
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Study Course Theme Plan
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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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Computer room
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2
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Topics
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Introduction to statistics. Type 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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Computer room
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2
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Topics
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Excel basics
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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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Computer room
|
2
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Topics
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Formulas in Excel
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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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Computer room
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2
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Topics
|
Descriptive statistics with Excel
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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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|---|---|---|
|
On site
|
Computer room
|
2
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Topics
|
Descriptive statistics with Excel
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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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|---|---|---|
|
On site
|
Computer room
|
2
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Topics
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Plots and diagrams
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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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|---|---|---|
|
On site
|
Computer room
|
2
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Topics
|
Pivot tables
|
-
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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Creation of tables and diagrams 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
|
Computer room
|
2
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Topics
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Hypotheses testing. Parametric tests
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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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Hypotheses testing. Parametric tests
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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
|
2
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Topics
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Comparing proportions
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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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|---|---|---|
|
On site
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Computer room
|
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
|
Computer room
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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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|---|---|---|
|
On site
|
Computer room
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2
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Topics
|
Independent work with 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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Computer room
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2
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Topics
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Independent work with data
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Bibliography
Required Reading
Verschuuren, G. M. N. Excel 2007 for Scientists and Engineers. 2nd ed., rev. and expanded. Uniontown, OH : Holy Macro! Books. 2008
Additional Reading
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
Winston, W. Microsoft Excel 2013 Data Analysis and Business Modeling, Microsoft Corporation, O’Reilly Media, Inc 2014
Kristapsone S. Statistikās analīzes metodes pētījumā. SIA "Biznesa augstskola Turība", 2020