Applied Economics Statistics


COURSE OUTLINE

  1. GENERAL
SCHOOL AGRICULTURAL AND FORESTRY SCIENCES
DEPARTMENT AGRICULTURAL DEVELOPMENT
LEVEL OF STUDIES 7
COURSE CODE ECO0002 SEMESTER 6TH, 8TH
COURSE TITLE APPLIED ECONOMIC STATISTICS
TEACHING ACTIVITIES
If the ECTS Credits are distributed in distinct parts of the course e.g. lectures, labs etc. If the ECTS Credits are awarded to the whole course, then please indicate the teaching hours per week and the corresponding ECTS Credits.
TEACHING HOURS PER WEEK ECTS CREDITS
Lectures and exercises  (3+2) 5
 
 
Please, add lines if necessary. Teaching methods and organization of the course are described in section 4.
COURSE TYPE

Background, General Knowledge, Scientific Area, Skill Development

Specialization
PREREQUISITES:

 

TEACHING & EXAMINATION LANGUAGE: Greek
COURSE OFFERED TO ERASMUS STUDENTS: Yes (in English)
COURSE URL:
  1. LEARNING OUTCOMES
Learning Outcomes
Please describe the learning outcomes of the course: Knowledge, skills and abilities acquired after the successful completion of the course.
Upon the completion of the course the students;

·        should become capable of applying statistics to confront problems of economic theory

General Skills
Name the desirable general skills upon successful completion of the module
Search, analysis and synthesis of data and information,

ICT Use

Adaptation to new situations

Decision making

Autonomous work

Teamwork

Working in an international environment

Working in an interdisciplinary environment

Production of new research ideas

Project design and management

Equity and Inclusion

Respect for the natural environment

Sustainability

Demonstration of social, professional and moral responsibility and sensitivity to gender issues

Critical thinking

Promoting free, creative and inductive reasoning

 

Analytical and Synthetical Thinking

  1. COURSE CONTENT
1.       Derived distributions, (x square, t-student, F distribution)

2.       sample distribution statistics,

3.       Estimation, Confidence Interval estimation for mean,

4.       two means, variance, proportions.

5.       Hypothesis Testing, Hypothesis Testing,Type I and Type II Errors,Power of a Test, Computing a test statistic,

6.       Making a decision about H0, Student t Distribution, Degrees of Freedom

7.       categorical data analysis,

8.       Homogeneity, Independence Test

9.       Goodness of Fit Test (Xsquare, Kolmogorov – Smirnov Tes)t

10.   linear models, OLS Estimation, Hypothesis Testing, Correlation Coefficient, Coefficient of Determinant,

11.   Simple Linear Models, Non linear Models

12.   Time series analysis

  1. LEARNING & TEACHING METHODSEVALUATION
TEACHING METHOD
Face to face, Distance learning, etc.
Face to face, Distance Learning
USE OF INFORMATION & COMMUNICATIONS TECHNOLOGY (ICT)
Use of ICT in Teaching, in Laboratory Education, in Communication with students
Power Point, Communication via email and eclass platform
TEACHING ORGANIZATION

The ways and methods of teaching are described in detail.

Lectures, Seminars, Laboratory Exercise, Field Exercise, Bibliographic research & analysis, Tutoring, Internship (Placement), Clinical Exercise, Art Workshop, Interactive learning, Study visits, Study / creation, project, creation, project. Etc.

 

The supervised and unsupervised workload per activity is indicated here, so that total workload per semester complies to ECTS standards.

Activity Workload/semester
Activity Semester workload
Lectures 39
Exercises 26
Individual study 60
Course total 125
(25-hour workload per credit unit)  
Student Evaluation

Description of the evaluation process

 

Assessment Language, Assessment Methods, Formative or Concluding, Multiple Choice Test, Short Answer Questions, Essay Development Questions, Problem Solving, Written Assignment, Essay / Report, Oral Exam, Presentation in audience, Laboratory Report, Clinical examination of a patient, Artistic interpretation, Other/Others

 

Please indicate all relevant information about the course assessment and how students are informed 

Written exams at the end of the semester both on theory and exercises

Two tests are taken within the semester and the average of the grade of those tests is multiplied by 0,3 and is added to the grade of the final test. The precondition for the validity of this bonus is the grade of the final test to be equal or over three. 2. Assignments are delegated to the students that are graded with ranking 0-2. The grade of this assignment is added to the final grade of the semester The precondition for the validity of this bonus is the grade of the final test to be equal or over three

 

 

  1. SUGGESTED BIBLIOGRAPHY
§  Koutroumanidis Th., Zafeiriou E., Malesios Ch., Statistics II (in Greek)

§  Manos B. Applied Statistics (in Greek)

§  Batzios Ch.Statistics in Education of Veterinary Science (in Greek)

 

 

 

 

 

 

ANNEX OF THE COURSE OUTLINE

 

Alternative ways of examining a course in emergency situations

 

Teacher (full name): Eleni Zafeiriou
Contact details: ezafeir@agro.duth.gr
Supervisors: (1) Yes
Evaluation methods: (2) Written Examination
Implementation Instructions: (3) The subjects of the exams will be provided through a file that will be uploaded in the field ‘projects’ for a specific time period in the eclass platform according to the program of exams.

The answers will be provided by the students through multimedia files.

Each exercise will be graded while the exam contribution will be 100%,

The exam is simultaneous for all the students

The participation in the exams can be done with the use of their institutional account.