Mathematical Statistics

Course Information
TitleΜΑΘΗΜΑΤΙΚΗ ΣΤΑΤΙΣΤΙΚΗ / Mathematical Statistics
Code0534
FacultySciences
SchoolMathematics
Cycle / Level1st / Undergraduate
Teaching PeriodWinter
CoordinatorFoteini Kolyva-Machaira
CommonNo
StatusActive
Course ID40000525

Programme of Study: UPS of School of Mathematics (2014-today)

Registered students: 1
OrientationAttendance TypeSemesterYearECTS
CoreElective Courses belonging to the selected specialization745.5

Class Information
Academic Year2015 – 2016
Class PeriodWinter
Faculty Instructors
Weekly Hours3
Class ID
600004704
Type of the Course
  • Scientific Area
Course Category
Specific Foundation / Core
Mode of Delivery
  • Face to face
Digital Course Content
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction, Examination)
Prerequisites
Required Courses
  • 0201 Calculus I
  • 0202 Calculus II
  • 0203 Calculus III
  • 0205 Calculus IV
  • 0502 Probability Theory I
  • 0503 Statistics
  • 0505 Probability Theory II
General Prerequisites
Probability theory,calculus
Learning Outcomes
The aim is to understeand and use statistical methods to solve real problems.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Make decisions
  • Work autonomously
  • Work in teams
  • Work in an interdisciplinary team
  • Generate new research ideas
  • Advance free, creative and causative thinking
Course Content (Syllabus)
Distributions of functions of random variables - Normal distribution and the derived distributions from the normal - The exponential family - Sufficiency of a statistic for a parameter or for functions of parameters. The Rao-Blackwel theorem - Completeness and uniqueness - Unbiased estimators with minimum variance - The Cramer-Rao inequality - Efficient statistics - Consistent statistics - Maximum likelihood and moment estimators and their properties - Prior and posterior distributions and Bayes estimators - The minimax principle - Interval estimation. General methods for construction of confidence intervals - Approximate confidence intervals - Confidence regions. Estimation of the probability density function (pdf)of a random variable X based on the Coefficient of VAriation.
Keywords
Point estimation, Interval estimation, Maximum likelihood, Unbiased estimators with minimum variance, Bayes
Educational Material Types
  • Notes
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Communication with Students
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures1505
Tutorial150.5
Total1655.5
Student Assessment
Student Assessment methods
  • Written Exam with Short Answer Questions (Formative, Summative)
  • Written Exam with Problem Solving (Formative, Summative)
Bibliography
Course Bibliography (Eudoxus)
- Μαθηματική Στατιστική-Εκτιμητική της Φ. Κολυβά-Μαχαίρα. - Εισαγωγή στη Στατιστική, Μέρος 2o των Χ. Δαμιανού, Μ. Κούτρα.
Last Update
09-11-2015