|SCHOOL||AGRICULTURAL AND FORESTRY SCIENCES|
|LEVEL OF STUDIES||7|
|COURSE CODE||ECO0002||SEMESTER||6TH, 8TH|
|COURSE TITLE||APPLIED ECONOMIC STATISTICS|
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.|
Background, General Knowledge, Scientific Area, Skill Development
|TEACHING & EXAMINATION LANGUAGE:||Greek|
|COURSE OFFERED TO ERASMUS STUDENTS:||Yes (in English)|
- 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
|Name the desirable general skills upon successful completion of the module|
|Search, analysis and synthesis of data and information,
Adaptation to new situations
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
Demonstration of social, professional and moral responsibility and sensitivity to gender issues
Promoting free, creative and inductive reasoning
Analytical and Synthetical Thinking
- 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
- LEARNING & TEACHING METHODS – EVALUATION
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|
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.
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
- 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|
|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.