1. GENERAL

SCHOOL

SCHOOL OF ECONOMIC SCIENCES

ACADEMIC UNIT

DEPARMENT OF ACCOUNTING AND FINANCE

LEVEL OF STUDIES

Undergraduate

COURSE CODE

BA103

SEMESTER

1

COURSE TITLE

INTRODUCTION TO STATISTICS
INDEPENDENT TEACHING ACTIVITIES WEEKLYTEACHING
HOURS
CREDITS
Lectures 3
Hours Lab 0
Hours Exercises 0

Total

3 6
COURSE TYPE Scientific Field, Compulsory
PREREQUISITE COURSES No
LANGUAGE OF INSTRUCTION and EXAMINATIONS Greek
IS THE COURSE OFFERED TO ERASMUS STUDENTS Yes (upon request)

COURSE WEBSITE (URL)

https://

2. LEARNING OUTCOMES

Learning outcomes

After successful completion of the course, students are expected to be able to:

1. Have knowledge of the basic concepts of probability theory and statistics.
2. Have knowledge of the basic statistical measures of central tendency and dispersion.
3. Has knowledge of the characteristics of the main theoretical probability distributions.
4. Understand the methodology of collecting, analyzing and presenting statistical data.
5. Apply methods of inference statistics (confidence intervals, statistical testing).

General Competences

• Decision-making
• Autonomous work
• Group work

3. SYLLABUS

The course aims at introducing the student to the basic principles of statistics and probability, present the methodology of collecting, organizing and presenting statistical data, describe the main probability distributions, solve simple problems of combinations, probability, confidence intervals, statistical tests, present regression analysis and analysis of variance and in general become acquainted with the statistical methods as a tool for business decision making.

The course content includes:

• Introduction to statistics, basic concepts
• Collection – presentation of statistical data (tables and diagrams)
• Statistical measures of central tendency
• Statistical measures of dispersion
• Permutations and combinations
• Basic concepts of probability theory
• Probability distributions
• Confidence intervals
• Statistical testing
• Estimation
• Regression
• Introduction to the analysis of variance

4. TEACHING and LEARNING METHODS - EVALUATION

DELIVERY
Face to face
USE OF INFORMATION AND COMMUNICATIONS TECHNOLOGY
Use of the electronic platform e-class
During office hours
Presentations are made using Power Point.
There is also the possibility of electronic communication via e-mail to the teacher.
Providing electronic teaching presentations to Students, via e-class.

TEACHING METHODS
Activity Semester workload
Lectures 30
Studying on distributed problem sets 65
Individual Study 49
Course total 144
Course total 288
STUDENT PERFORMANCE EVALUATION • Mid-term Exam 30%
• Final Exam(multiple choice, short-answer questions, problem solving) 70%

5. SUGGESTED BIBLIOGRAPHY

-Suggested bibliography:
Recommended Book Resources:
• ΣαριαννίδηςΝίκοςκαι Γιώργος Κοντέος, 2016. Στατιστική, εκδόσεις Αλέξανδρος ΙΚΕ, Κοζάνη. ISBN: 9786188277816
• Fourastie, J., Laslier, J. - F., 2001. Πιθανότητες και Στατιστική. Εκδόσεις Πατάκη, Αθήνα. ISBN: 978-960-16-0066-6
• Σιάρδος Γ., 2005. Μέθοδοι Στατιστικής Πολυμεταβλητής Ανάλυσης. Εκδόσεις Σταμούλη Α.Ε.ISBN: 978-960-351-622-8
• D. S. Yates, D. S. Starnes, D. S. Moore (2004) Statistics through Applications. W. H. Freeman. ISBN-10: 0716747723, ISBN-13: 978-0716747727
• D. S. Moore (2007). The Basic Practice of Statistics. W. H. Freeman. ISBN-10: 0716770628, ISBN-13: 978-0716770626
-Related academic journals:

 

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