Title  ΣΤΑΤΙΣΤΙΚΗ / STATISTICS 
Code  114 
Faculty  Engineering 
School  Mechanical Engineering 
Cycle / Level  1st / Undergraduate 
Teaching Period  Winter 
Coordinator  Georgios Tagaras 
Common  Yes 
Status  Active 
Course ID  20000305 
Programme of Study: UPS of School of Mechanical Engineering
Registered students: 462
Orientation  Attendance Type  Semester  Year  ECTS 

Core  Compulsory Course  3  2  6 
Academic Year  2019 – 2020 
Class Period  Winter 
Faculty Instructors 

Instructors from Other Categories  
Weekly Hours  5 
Class ID  600149862

Type of the Course
 Background
Course Category
General Foundation
Mode of Delivery
 Face to face
Digital Course Content
 eStudy Guide https://qa.auth.gr/en/class/1/600149862
 eLearning (Moodle): https://elearning.auth.gr/course/view.php?id=7388
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
 Greek (Instruction, Examination)
Learning Outcomes
Understanding and ability to apply the basic concepts and techniques of probability theory and statistical inference.
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)
Descriptive statistics: data summary and presentation, frequency distribution, histogram, characteristic values.
Probability and probability distributions: basic concepts, events, conditional probability and Bayes theorem. Probability distributions, discrete and continuous random variables, expected value, variance and standard deviation, moment generating function. Important distributions: binomial, geometric, Poisson, uniform, exponential, gamma, normal distribution and the central limit theorem, Student, X2 and F distributions.
Statistical estimation: sampling distributions, point estimation, properties of estimators, confidence intervals, required sample size.
Statistical hypotheses: type I and type II errors, hypotheses on parameters, goodness of fit tests.
Simple linear regression.
Keywords
Statistics, Probability
Educational Material Types
 Book
Use of Information and Communication Technologies
Use of ICT
 Use of ICT in Course Teaching
 Use of ICT in Communication with Students
Description
Problem solving on the computer using spreadsheets and specialized software.
Educational material and information about the course are available at eLearning (https://elearning.auth.gr/course/view.php?id=7388).
Course Organization
Activities  Workload  ECTS  Individual  Teamwork  Erasmus 

Lectures  65  2.2  ✓  
Reading Assigment  100  3.3  ✓  ✓  
Written assigments  11  0.4  ✓  
Exams  4  0.1  ✓  
Total  180  6 
Student Assessment
Description
The final grade (M) is a combination of the grade in the final exam (B) and that of the homework project (E) as follows:
 If B < 4,3 then M = B.
 If Β ≥ 4,3 then Μ = Β + (0,1)Ε.
Student Assessment methods
 Written Exam with Multiple Choice Questions (Summative)
 Written Exam with Short Answer Questions (Summative)
 Written Exam with Extended Answer Questions (Summative)
 Written Assignment (Summative)
 Homework (Summative)
Bibliography
Course Bibliography (Eudoxus)
1. Ζιούτας, Γ.Χ. "Πιθανότητες και στατιστική για μηχανικούς", εκδ. Σοφία, Θεσσαλονίκη, 2019.
2. Ζαχαροπούλου, Χ. "Στατιστική, μέθοδοι – εφαρμογές, τόμος Α’", εκδ. Σοφία, Θεσσαλονίκη, 2012.
3. Αγγελής, Β. και Δημάκη, Κ. "Στατιστική,τόμος Α'", εκδ. Σοφία, Θεσσαλονίκη, 2011.
4. Ψωινός, Δ.Π. "Στατιστική", εκδ. Ζήτη, Θεσσαλονίκη, 1999.
5. Μυλωνάς, Ν. και Παπαδόπουλος, Β. "Πιθανότητες & Στατιστική για μηχανικούς", εκδ. Τζιόλα, Θεσσαλονίκη, 2017.
Additional bibliography for study
 Montgomery, D.C., Runger, G.C., Applied Statistics and Probability for Engineers, Wiley, 2006.
 Montgomery, D.C., Runger, G.C., Hubele, N.F., Engineering Statistics, Wiley, 2007.
Last Update
11102019