STATISTICAL COMPUTING
| Title | ΣΤΑΤΙΣΤΙΚΗ ΥΠΟΛΟΓΙΣΤΙΚΗ / STATISTICAL COMPUTING |
| Code | NNA-08-06 |
| Faculty | Sciences |
| School | Informatics |
| Cycle / Level | 1st / Undergraduate |
| Teaching Period | Spring |
| Coordinator | Eleftherios Angelis |
| Common | No |
| Status | Active |
| Course ID | 600018370 |
Programme of Study: PPS-Tmīma Plīroforikīs (2019-sīmera)
Registered students: 36
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| GENIKĪ KATEUTHYNSĪ | YPOCΗREŌTIKO KATA EPILOGĪ | 8 | 4 | 5 |
| Academic Year | 2020 – 2021 |
| Class Period | Spring |
| Faculty Instructors |
|
| Weekly Hours | 3 |
| Class ID | 600180127
|
Course Type 2021
Specialization / Direction
Course Type 2016-2020
- Scientific Area
Course Type 2011-2015
Knowledge Deepening / Consolidation
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600180127
- eLearning (Moodle):
Language of Instruction
- Greek (Instruction, Examination)
Prerequisites
General Prerequisites
Basics in probabilities and statistics
Learning Outcomes
Cognitive: Programming techniques in statistical programming language (R) in combination with advanced statistical methodologies. Particular emphasis on the construction of appropriate statistical models to describe complex relationships.
Skills: The student learns to use an advanced statistical language in order to be able to interpret data analysis results but also to construct models that explain relationships and are used in predictions.
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Make decisions
- Work autonomously
- Generate new research ideas
Course Content (Syllabus)
Statistical programming techniques with R. Data structures for statistical analysis. Description and visualization of multivariate data. Hypotheses tests and multivariate methodologies focusing on algorithmic techniques for distribution estimation, random number generation, confidence intervals and hypothesis tests with resampling, non parametric regression, etc.
Keywords
Statistics, Statistical Programming, R language
Educational Material Types
- Slide presentations
- Book
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 39 | ✓ | |||
| Reading Assigment | 98 | ✓ | |||
| Project | 10 | ✓ | |||
| Exams | 3 | ✓ | |||
| Total | 150 |
Student Assessment
Description
Mid-term and final exams, project
Student Assessment methods
- Written Assignment (Formative, Summative)
- Written Exam with Problem Solving (Formative, Summative)
Bibliography
Course Bibliography (Eudoxus)
Εισαγωγή στη Στατιστική Ανάλυση με το R, Michael J. Crawley, 2014, Εκδόσεις : Broken Hill, Π. Χ. Πασχαλίδης
Last Update
10-04-2022
