STATISTICS II

Course Information
TitleΣΤΑΤΙΣΤΙΚΗ II / STATISTICS II
Code12ΥΒ03
FacultySocial and Economic Sciences
SchoolEconomics
Cycle / Level1st / Undergraduate
Teaching PeriodSpring
CoordinatorAndreas Mattas
CommonYes
StatusActive
Course ID100001409

Programme of Study: UPS School of Economics (2013-today)

Registered students: 984
OrientationAttendance TypeSemesterYearECTS
KORMOSCompulsory Course216

Class Information
Academic Year2019 – 2020
Class PeriodSpring
Faculty Instructors
Weekly Hours4
Class ID
600147357
Course Type 2016-2020
  • Background
  • General Knowledge
Course Type 2011-2015
General Foundation
Mode of Delivery
  • Face to face
Language of Instruction
  • Greek (Instruction, Examination)
Learning Outcomes
After finishing the course, the student will be able to A) Understand basic statistical concepts and methods of inferential statistics B) Execute parametric tests and non-parametric tests C) Acknowledge and manage problems of the sampling methods, D) Solve problems of linear regression E) Use further statistical software packages and tools for data analyses
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
  • Advance free, creative and causative thinking
Course Content (Syllabus)
Statistical Inference: Sampling, Estimation, Hypothesis Testing. Goodness of fit tests, tests for bivariate relationships. Simple linear regression. Syllabus: - Sampling methods and sampling distributions for the mean, variance, and proportion. - Point and interval estimation for the mean, variance, and proportion. - One sample tests of hypotheses for the mean, variance, and proportion. - Univariate goodness of fit tests. - Chi-square tests of independence in two-way contingency tables. - Bivariate Pearson product moment and rank correlation coefficients. Hypothesis tests for bivariate correlation. - Simple linear regression.
Keywords
Inference, estimation, hypothesis testing, correlation, regression.
Educational Material Types
  • Notes
  • Slide presentations
  • Multimedia
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Laboratory Teaching
  • Use of ICT in Communication with Students
Description
- Powerpoint presentations - Statistical software (SPPS) at the Lab - Course webpage with supplementary teaching material
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures541.9
Laboratory Work521.9
Project100.4
Written assigments521.9
Total1686
Student Assessment
Description
1. Written examination at the end of the semester: (a) multiple coice questions (5 grade points) and (b) exercises (5 grade points). 2. Participation to Lab sessions, tutorials, and assignments (up to 2 grade points, conditional on a pass-mark at the final examination).
Student Assessment methods
  • Written Exam with Multiple Choice Questions (Summative)
  • Written Assignment (Summative)
  • Written Exam with Problem Solving (Summative)
  • Labortatory Assignment (Summative)
Bibliography
Course Bibliography (Eudoxus)
Βιβλίο [22768741]: ΕΦΑΡΜΟΣΜΕΝΗ ΣΤΑΤΙΣΤΙΚΗ, ΤΑΜΠΑΚΗΣ ΝΙΚΟΛΑΟΣ, ΧΑΨΑ ΞΑΝΘΙΠΠΗ Λεπτομέρειες Βιβλίο [59381285]: Εισαγωγή στη Στατιστική, Νικόλαος Σαριαννίδης, Γεώργιος Κοντέος Λεπτομέρειες Βιβλίο [77120360]: ΣΤΑΤΙΣΤΙΚΗ ΤΟΜΟΣ Α', Ζ' ΕΚΔΟΣΗ, ΖΑΧΑΡΟΠΟΥΛΟΥ ΧΡΥΣΟΥΛΑ Λεπτομέρειες
Last Update
20-01-2021