MULTIVARIATE STATISTICS

Course Information
TitleΣΤΑΤΙΣΤΙΚΗ ΠΟΛΛΩΝ ΜΕΤΑΒΛΗΤΩΝ / MULTIVARIATE STATISTICS
Code208
FacultyEngineering
SchoolMechanical Engineering
Cycle / Level1st / Undergraduate
Teaching PeriodWinter
CoordinatorGeorgios Tagaras
CommonNo
StatusActive
Course ID20000307

Programme of Study: UPS of School of Mechanical Engineering

Registered students: 55
OrientationAttendance TypeSemesterYearECTS
EnergyElective Courses belonging to the other745
Design and StructuresElective Courses belonging to the other745
Industrial ManagementCompulsory Courses belonging to the selected specialization745

Class Information
Academic Year2014 – 2015
Class PeriodWinter
Faculty Instructors
Weekly Hours6
Class ID
20051652
Type of the Course
  • Background
Mode of Delivery
  • Face to face
Language of Instruction
  • Greek (Instruction, Examination)
Prerequisites
Required Courses
  • 114 STATISTICS
General Prerequisites
The course "Statistics" is not formally a prerequisite but sufficient knowledge of its content is essential for the effective understanding of the concepts in "Multivariate Statistics".
Learning Outcomes
The main objective is the understanding of the theory fundamentals and the ability for practical implementation of statistical analysis methods in problems where more than one random variables are involved. In parallel, the course aims at deepening the understanding of basic concepts 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
Course Content (Syllabus)
Two and higher-dimensional random variables: joint, marginal and conditional distributions. Covariance and correlation. Independent random variables, sums of independent random variables. The bivariate normal distribution. Analysis of variance: the fixed and random effects models for one factor. Design of statistical experiments: factorial and fractional factorial experiments, design and statistical analysis. Response surface methodology. Simple and multiple linear regression, nonlinear regression, correlation.
Keywords
Statistics, Probability
Educational Material Types
  • Notes
  • Book
  • Computer software
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Communication with Students
Description
Utilization of specialized computer software for problem solving. Posting of announcements, notes and information regarding the course at eClass.
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures652.2
Interactive Teaching in Information Center
Written assigments
Total652.2
Student Assessment
Description
The final grade M is a combination of the grades in the final written examination (T), the midterm examination (Π) and the project/homework (E) as follows: • If either Τ < 4,5 or (Τ+Π)/2 < 4, then the final grade is Μ = (0,8)Τ. • In every other case the final grade is Μ = max {(0,6)Τ + (0,3)Π + (0,2)Ε, (0,8)T}.
Student Assessment methods
  • Written Exam with Short Answer Questions (Summative)
  • Written Assignment (Summative)
  • Problem solving (Summative)
Bibliography
Course Bibliography (Eudoxus)
1. Χαλικιάς, Ι.Γ. "Στατιστική, Μέθοδοι ανάλυσης για επιχειρηματικές αποφάσεις", εκδ. Rosili, Αθήνα, 2010. 2. Keller, G. "Στατιστική για οικονομικά και διοίκηση επιχειρήσεων", εκδ. Επίκεντρο, Θεσσαλονίκη, 2010.
Additional bibliography for study
- Antony, J., Kaye, M., Experimental Quality, Kluwer, 1999. - Cobb, G.W., Introduction to Design and Analysis of Experiments, Springer, 2002. - Montgomery, D.C., Design and Analysis of Experiments, Wiley, 2008. - 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
26-07-2013