# ANALYSIS AND DATA PROCESSING

 Title ΑΝΑΛΥΣΗ ΚΑΙ ΕΠΕΞΕΡΓΑΣΙΑ ΔΕΔΟΜΕΝΩΝ / ANALYSIS AND DATA PROCESSING Code ΜΥΠ751 Faculty Sciences School Physics Cycle / Level 2nd / Postgraduate Teaching Period Winter Common No Status Active Course ID 40000209

 Academic Year 2018 – 2019 Class Period Winter Faculty Instructors Dimitris Kugiumtzis 3hrs Weekly Hours 3 Class ID 600133688
Course Type 2016-2020
• Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
• Face to face
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
• Greek (Instruction, Examination)
• English (Instruction, Examination)
Learning Outcomes
The scope of the course is the introduction of concepts and methods of data analysis, as well as their application to real-world problems. Within the framework of application the scope is the use of relevant software.
General Competences
• Apply knowledge in practice
• Retrieve, analyse and synthesise data and information, with the use of necessary technologies
• Work autonomously
Course Content (Syllabus)
Introduction: definitions, data, examples. Probability and random variables: fundamentals on probability, distributions, parameters of distributions, basic distributions. Elements of statistics: parameter estimation and hypothesis testing. Uncertainty and measurement error: systematic and random errors, error propagation. Correlation and regression: correlation, simple and multiple regression, linear and nonlinear regression. Time series: basic characteristics of time series, correlation in time series.
Keywords
data analysis, statistics, probability, time series
Educational Material Types
• Notes
• Slide presentations
Use of Information and Communication Technologies
Use of ICT
• Use of ICT in Course Teaching
Description
A practical lab on the computational environment Matlab.
Course Organization
Lectures180.6
Laboratory Work180.6
Total361.2
Student Assessment
Description
Lab exam (the computational environment Matlab): 50% of the final mark Project on the basis of the computational environment Matlab: 50% of the final mark
Student Assessment methods
• Labortatory Assignment (Formative, Summative)
• Exam on computer
Bibliography
Course Bibliography (Eudoxus)
1. Σημειώσεις "Ανάλυση δεδομένων", Δ. Κουγιουμτζής, 2012 (δες http://users.auth.gr/dkugiu/Teach/DataAnalysis/index.html)