Data Analysis and Visualization in Spreadsheets (Theory/Practice)
| Title | Ανάλυση και Οπτικοποίηση Δεδομένων σε Υπολογιστικά Φύλλα (Θ/Α) / Data Analysis and Visualization in Spreadsheets (Theory/Practice) |
| Code | AGE2000 |
| Faculty | Social and Economic Sciences |
| School | Journalism and Mass Communications |
| Cycle / Level | 1st / Undergraduate |
| Teaching Period | Winter |
| Coordinator | Constantinos Barbargires |
| Common | Yes |
| Status | Active |
| Course ID | 600020546 |
Programme of Study: ANPPS Tmīmatos Dīmosiografías kai M.M.E. (2020-2021)
Registered students: 0
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| ''DĪMOSIOGRAFIAS'' | Elective Courses | Winter/Spring | - | 5 |
| ''MESŌN EPIKOINŌNIAS'' | Elective Courses | Winter/Spring | - | 5 |
| Academic Year | 2024 – 2025 |
| Class Period | Spring |
| Instructors from Other Categories |
|
| Weekly Hours | 3 |
| Total Hours | 39 |
| Class ID | 600268484
|
Course Type 2021
Skills Development
Course Type 2016-2020
- General Knowledge
- Skills Development
Course Type 2011-2015
General Foundation
Mode of Delivery
- Face to face
Digital Course Content
Language of Instruction
- Greek (Instruction, Examination)
Prerequisites
Required Courses
- AGE1100 Information Technologies and Applications in Communication
Learning Outcomes
Students who will have successfully completed the course, will be able to:
- Use spreadsheet software effectively.
- Perform basic data analysis on spreadsheets.
- Create charts to visualize data on spreadsheets.
- Use decision-making tools for script analysis and goal search.
- Import external data into spreadsheets from other data files (e.g., CSV files), databases, or the Web, to further analyze and visualize them.
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Make decisions
- Work autonomously
- Advance free, creative and causative thinking
Course Content (Syllabus)
The course is an introduction to the analysis and visualization of data in spreadsheets, and it is supported by extensive bibliography (both Greek and foreign) in electronic form, as well as special audiovisual educational material, which is presented during the lessons.
In particular, the course material includes: Introduction to spreadsheets, spreadsheet software (Microsoft Excel, LibreOffice Calc, Google Sheets), Formulas, Functions, Charts, Datasets, Tables, Subtotals, PivotTables, PivotCharts, What-If Analysis, Special Functions, Statistical Functions, Multi-spreadsheet Management, External Data Entry, Web Queries and XML language, Collaboration and distribution of spreadsheets.
Keywords
spreadsheets, data analysis, data visualization, Microsoft Excel, LibreOffice Calc, Google Sheets
Educational Material Types
- Notes
- Slide presentations
- Video lectures
- Multimedia
- Book
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Laboratory Teaching
- Use of ICT in Communication with Students
- Use of ICT in Student Assessment
Description
The course is supported by an independent web-site, at the following address: [http://veria.jour.auth.gr:82/course/view.php?id=4 ]. There is free access for everyone to the home-page, the news page, and the course summary, while for the other areas of the site (course material and bibliography, weekly-lessons program and contents, evaluation methods and results, subjects of projects and past exams), the access is allowed by using personalized access codes for every student.
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 24 | ✓ | |||
| Laboratory Work | 12 | ✓ | |||
| Reading Assigment | 50 | ✓ | |||
| Tutorial | 3 | ✓ | |||
| Project | 30 | ✓ | |||
| Exams | 2 | ✓ | |||
| Total | 121 |
Student Assessment
Description
The final grade of the course is calculated only if there are no absences in the laboratory lessons and it is the result of the individual grades in the following:
1. Exercises during laboratory lessons (20%)
2. Data analysis and visualization project in Microsoft Excel (20%)
3. Final theoretical examination (30%)
4. Final practical examination (30%)
Remarks
(a) Each individual grade, in order to count towards the final score, should be greater than the corresponding base-score, which is set at half of the corresponding maximum score.
b) All laboratory exercises are mandatory. Only two (2) very well-justified absences may be replenished during the semester, after consultation with the instructor, and at the latest within one week of the respective absence.
Ensuring transparency in the assessment of student performance
Students are informed on a weekly basis about their performance in the laboratory exercises they perform at each (weekly) laboratory lesson by receiving a personalized e-mail in the account provided by the University, and have the possibility -in the context of office hours- to be further informed about their errors and omissions. In the same way they are informed of their performance and their errors / omissions both in the project they deliver and in the final examinations of the theoretical and practical part of the course at the end of the semester.
Student Assessment methods
- Written Exam with Extended Answer Questions (Summative)
- Labortatory Assignment (Formative, Summative)
Bibliography
Additional bibliography for study
- Steven M. Freund, Joy L. Starks, and Eric Schmieder, "Microsoft Office 365 Excel 2016: Comprehensive" (Shelly Cashman Series), ISBN: 978-1-305-87072-7, Cengage Learning, 2017.
- David Slager, "Essential Excel 2016: A Step-by-Step Guide", ISBN: 978-1-4842-2160-0, Apress, 2016.
- Adam Aspin, "High Impact Data Visualization in Excel with Power View, 3D Maps, Get & Transform and Power BI", 2nd Edition, ISBN: 978-1-4842-2399-4, Apress, 2016.
- Curtis D. Frye, "Microsoft Excel 2016, Step by Step", ISBN 978-0-7356-9880-2, Microsoft Press, 2015.
- Cole Nussbaumer Knaflic, "Storytelling with Data - A data visualization guide for business professionals", ISBN: 978-1-119-00225-3, John Wiley & Sons, Inc., 2015.
- Paul McFedries, "Excel Data Analysis: Your visual blueprint for analyzing data, charts, and PivotTables", 4th Edition, ISBN: 978-1-118-51714-7, Wiley Publishing, Inc., 2013.
- Riccardo Mazza, "Introduction to Information Visualization", ISBN: 978-1-84800-218-0, Springer, 2009.
Last Update
06-03-2025
