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Data Processing and Analysis in Microsoft Excel
Study Course Description
Course Description Statuss:Approved
Course Description Version:1.00
Study Course Accepted:29.04.2024 13:38:07
| Study Course Information | |||||||||
| Course Code: | SL_133 | LQF level: | All Levels | ||||||
| Credit Points: | 2.00 | ECTS: | 3.00 | ||||||
| Branch of Science: | Mathematics; Theory of Probability and Mathematical Statistics | Target Audience: | Psychology; Dentistry; Pharmacy; Medicine; Rehabilitation; Political Science; Communication Science; Nursing Science; Public Health | ||||||
| Study Course Supervisor | |||||||||
| Course Supervisor: | Dina Barute | ||||||||
| Study Course Implementer | |||||||||
| Structural Unit: | Statistics Unit | ||||||||
| The Head of Structural Unit: | |||||||||
| Contacts: | 14 Baložu street, Riga, +371 67060897, statistika rsu[pnkts]lv, www.rsu.lv/en/statistics-unit | ||||||||
| Study Course Planning | |||||||||
| Full-Time - Semester No.1 | |||||||||
| Lectures (count) | 0 | Lecture Length (academic hours) | Total Contact Hours of Lectures | 0 | |||||
| Classes (count) | 15 | Class Length (academic hours) | 2 | Total Contact Hours of Classes | 30 | ||||
| Total Contact Hours | 30 | ||||||||
| Study course description | |||||||||
| Preliminary Knowledge: | Secondary school background in mathematics and informatics. | ||||||||
| 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. | ||||||||
| Topic Layout (Full-Time) | |||||||||
| No. | Topic | Type of Implementation | Number | Venue | |||||
| 1 | Introduction to statistics. Type of data | Classes | 1.00 | computer room | |||||
| 2 | Excel basics | Classes | 1.00 | computer room | |||||
| 3 | Formulas in Excel | Classes | 1.00 | computer room | |||||
| 4 | Descriptive statistics with Excel | Classes | 2.00 | computer room | |||||
| 5 | Plots and diagrams | Classes | 1.00 | computer room | |||||
| 6 | Pivot tables | Classes | 1.00 | computer room | |||||
| 7 | Creation of tables and diagrams according to data type | Classes | 1.00 | computer room | |||||
| 8 | Hypotheses testing. Parametric tests | Classes | 2.00 | computer room | |||||
| 9 | Comparing proportions | Classes | 1.00 | computer room | |||||
| 10 | Correlation and linear regression | Classes | 2.00 | computer room | |||||
| 11 | Independent work with data | Classes | 2.00 | computer room | |||||
| Assessment | |||||||||
| Unaided Work: | 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. | ||||||||
| Assessment Criteria: | 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). | ||||||||
| Final Examination (Full-Time): | Exam | ||||||||
| Final Examination (Part-Time): | |||||||||
| Learning Outcomes | |||||||||
| Knowledge: | 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: | 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. | ||||||||
| Competencies: | 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. | ||||||||
| Bibliography | |||||||||
| No. | Reference | ||||||||
| 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 | ||||||||
| 3 | Kristapsone S. Statistikās analīzes metodes pētījumā. SIA "Biznesa augstskola Turība", 2020 | ||||||||
