POLITICAL SCIENCE

Course Code
03.04Κ
ECTS Credits
6
Semester
3rd Semester
Course Category

Compulsory

Compulsory

Course Description
GENERAL
TEACHING METHODS: TEACHING HOURS (WEEKLY)

Lectures

Laboratory Exercises

 

2

1

COURSE TYPE: General Background
COURSE PREREQUISITES: None
TEACHING LANGUAGE: Greek
THE COURSE IS OFFERED TO ERASMUS STUDENTS: No
LEARNIING RESULTS
Course Description and Learning Objectives

Students should have the following skills after completing the course:

Knowledge: Understanding and describing course concepts such as the distribution functions for discrete and continuous random variables, sampling distribution, hypothesis testing, parametric and nonparametric tests.

Abilities: To recommend fundamental statistical tools and data analysis strategies for making business decisions. Statistical thinking should be integrated into administrative practice. Analyze, synthesize, and develop evaluative judgments about Business Administration challenges.

Skills: To organize, present, and analyze administrative and financial statistics using proper statistical methodologies.

Competencies

Searching, analysing and synthesising data and information using the necessary technologies

- Autonomous work

- Working in an interdisciplinary environment

- Exercising critical and self-critical thinking

- Promotion of free, creative and deductive thinking

CONTENT

It is a fundamental introductory course in inferential statistics concepts, principles, and methods. Introduces students to random variables and probability distributions, equipping them with the knowledge needed to understand inductive statistics and familiarizing them with the use of statistical analysis methods in a variety of sectors, with a focus on business management and economics.

The course is divided into 13 sections.

Discrete and continuous random variables, distribution functions

Expected value and variance of random variables

Discrete probability distribution: Binomial

Discrete probability distribution: Poisson

Continuous probability distribution: Normal

Random sampling

Sampling distribution. The central limit theorem

Confidence interval for mean and proportion

Hypothesis testing

Introduction to one-way analysis of variance

Introduction to nonparametric tests

Contingency tables

Simple linear regression

 

The numbering corresponds to the week of the course.

TEACHING and LEARNING METHODS - EVALUATION
TEACHING METHOD

i. Face-to-face lectures

ii. Face to face - Solving tutorial exercises.

Posting material for further study and solving exercises on the e-class platform

 

USE OF INFORMATION AND COMMUNICATION TECHNOLOGIES Support for the learning process and communication with students via the electronic platform e-class
METHODS OF INSTRUCTION
Method Semester workload
Lectures 26
Tutoring – Classroom exercises 13

Independent Exercise Solution

Independent Study

39

72

 

 

Total workload in hours 150
STUDENT LEARNING ASSESMENT

- The evaluation will be carried out in three different methods in Greek:

1. A mid-term assessment in the 7th or 8th week (20 %).

2. Individual tasks (10%) that will be graded in the following manner: Ability to solve problems and give a public presentation

3. A written final exam (70%) that covers the following topics:

- Multiple choice questions

- Comparative analysis of theoretical aspects

- Problem-solving skills

 

RECOMMENDED-BIBLIOGRAPHY

1. Downing D., Clark J. Business Statistics, 4th ed./2010, KLEIDARITHMOS EPE Publishing, ISBN: 978-960-461-390-8.

2. Gnardellis X. Applied statistics, 2nd Ed./2019, Ed. A. Papazisis, ISBN: 978-960-02-3466-4.

3. Bakura A. Introduction to Statistics, 2013, Ed. DISIGMA, ISBN: 978-960-9495-29-5

4. Keller, G. Statistics for Finance and Business Administration, 2010 Ed. Epicenter, ISBN: 978-960-45-8206-8.