Statistics II

Course ID: 
ECO_122N
Semester: 
Year of Study: 
Category: 
For Erasmus Students: 
Yes

Learning Outcomes

By the end of this course the student will be able to:

  • Have basic knowledge of theoretical probability distributions which constitute an essential methodological tool.
  • Understand and be able to apply essential statistical inference. This implies that students should develop critical thinking on decision making.
  • Understand and apply basic regression analysis to decision making

By the end of this course the student will have developed the following skills:

  • Ability to exhibit knowledge and understanding of the essential facts, concepts, theories and applications which are related to statistical inference and regression analysis.
  • Ability to adopt and apply methodology for solving problems in the fields of statistical inference and regression analysis.
  • Ability to use computational techniques in the aforementioned fields.
  • Ability to interact with experts in statistics.

Course Contents

  • Theory:
    • Large sample statistical inference. Sampling distributions. Means, difference between two means, proportions, difference between two proportions. Confidence intervals. Statistical testing. Small sample statistical inference. Student's t probability distribution. Means, difference between two means, paired difference test, proportions, difference between two proportions. Inferences about a population variance. The χ2 probability distribution. Comparing two population variances. The F probability distribution. Introduction to simple and multiple regressions. The method of least-squares. Testing the utility of a model. Model building. Elements of time-series analysis.

Teaching Activities

Lectures (4 hours per week) and Tutorials (2 hour per week)

Teaching Organization

Activity

Semester workload

Lectures (4 hours per week x 13 weeks)

52 hours

Tutorials (2 hour per week x 13 weeks) - solving of representative problems

26 hours

Hours for private study

122

Total number of hours for the Course (25 hours of work-load per ECTS credit)

200 hours (total student work-load)

Assessment

The overall course grade is the sum of

a) final exam grade, plus

b) 20 percent of the mid-term exam grade

Course Info

Teaching Hours: 
6 hours per week
ECTS Credits: 
8.00
Teaching Credits: 
5.00
Weight: 
2.00
Language: 
Teaching Method: 
Indicative Prerequisites: 

Current Tutors

Instructor: 

Polymenis Athanasios

Assistant Professor
Polymenis Athanasios
Field of Expertise: 
Statistics, Mathematics, Econometrics
Organic Unit / Lab: 
Laboratory of Quantitative Economics and Information Systems
E-mail: 
Telephone: 
Office Hours: 
Tuesday 16.00-15.00
Wednesday 10.00-12.00

Reading List

Reading Recommendations: 
Keller, G. 2010. Στατιστική για οικονομικά και διοίκηση επιχειρήσεων. Εκδ. Επίκεντρο, Θεσσαλονίκη.
Aczel, D. A. & Sounderpandian, J. 2016. Στατιστική σκέψη στον κόσμο των επιχειρήσεων. Ιατρικές Εκδ. Π.Χ. Πασχαλίδης, Αθήνα
Χάλκος, Ε. Γ. 2000. Στατιστική-θεωρία εφαρμογές και χρήση προγραμμάτων σε Η/Υ. Εκδ. Τυπωθήτω, Αθήνα
Bibliography Recommendations: 
Canavos, G. C. & Miller, D. M. 1993. Wadswarth Pub Co. An introduction to modern business statistics. ISBN: 9780534168421
Keller, G. 2014. Southwestern College Pub. Statistics for management and economics