Course Information
TitleΒΙΟΜΕΤΡΙΑ / Biometry
FacultyAgriculture, Forestry and Natural Environment
Cycle / Level2nd / Postgraduate, 3rd / Doctorate
Teaching PeriodSpring
Course ID420000558

Class Information
Academic Year2017 – 2018
Class PeriodWinter
Faculty Instructors
Weekly Hours3
Total Hours78
Class ID
Course Type 2016-2020
  • Background
  • Scientific Area
  • Skills Development
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
  • Face to face
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction, Examination)
  • English (Instruction, Examination)
General Prerequisites
Students should be familiar with the use of computers. Students should have attended courses on Statistics and Agricultural Experimentation.
Learning Outcomes
Upon completion of this course, students will be able to: 1) Explain fundamental ideas of Probability and Statistics and the theory behind the commonly used statistical techniques. 2) Apply suitable statistical techniques correctly for solving biological problems. 3) Analyze data using common statistical software and interpret outputs. 4) Prepare statistical reports and make presentations. 5) Communicate with a statistician.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Adapt to new situations
  • Make decisions
  • Work autonomously
  • Work in teams
  • Work in an international context
  • Work in an interdisciplinary team
  • Generate new research ideas
  • Design and manage projects
  • Respect natural environment
  • Be critical and self-critical
  • Advance free, creative and causative thinking
Course Content (Syllabus)
Introduction to Biometry. Descriptive and Inferential Statistics. Confidence intervals. Parametric and non-Parametric statistical tests. Agricultural experimentation and introduction to Analysis of Variance (ANOVA). Introduction to linear models (general/mixed). Methodology for setting up and statistically analysing data coming from simple experiments (Completely Randomized Design, Randomized Complete Block Design, Latin Square Design, Balanced Lattice Design). Methodology for setting up and statistically analysing data coming from factorial experiments (with crossed and/or nested factor structure). Statistical analysis of data coming from split plot designs and designs with repeated measures. Statistical analysis of data coming from designs combined over locations and/or years. Multiple linear and non linear regression. Introduction to Multivariate-Multidimensional Data Analysis. Principal Components Analysis, Hierarchical Cluster Analysis, biplot-analysis, Discriminant Analysis. Statistical Analyses for categorical data. Contingency tests. Introduction to Correspondence Analysis. Analysis of biological data with statistical software.
Experimental designs, Analysis of Variance, Linear and non linear Regression, Multivariate Data Analysis, Statistical Software
Educational Material Types
  • Notes
  • Slide presentations
  • Multimedia
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Communication with Students
Powerpoint, video, Excel, SPSS, educational software-tutorial, email.
Course Organization
Reading Assigment
Written assigments
Student Assessment
80% written exams 20% Project
Student Assessment methods
  • Written Exam with Multiple Choice Questions (Formative, Summative)
  • Written Exam with Short Answer Questions (Formative, Summative)
  • Written Assignment (Formative, Summative)
  • Performance / Staging (Formative)
  • Written Exam with Problem Solving (Formative, Summative)
Course Bibliography (Eudoxus)
1) Φωτιάδης, Ν. (1995). "Εισαγωγή στη Στατιστική για βιολογικές επιστήμες". Θεσσαλονίκη: University Studio Preee (Κωδικός Εύδοξος: 17225). 2) Φασούλας, Α. (2008). "Στοιχεία Πειραματικής Στατιστικής". Θεσσαλονίκη: Εκδόσεις Γαρταγάνη.(Κωδικός Εύδοξος: 1944).
Additional bibliography for study
1) Steel, R., Torrie, J. & Dickey, D. (1997). Principles and Procedures of Statistics: A Biometrical Approach. Third Edition. Singapore: McGraw-Hill Book Company. 2) Gomez, K. & Gomez, A. (1984). Statistical Procedures for Agricultural Research. Singapore: John Willey & Sons, Inc. 3) Zar, J. (1996). Biostatistical Analysis. New Jersey: Prentice-Hall International, Inc. 4) Μενεξές, Γ. & Οικονόμου, Α. (2002). Σφάλματα και Παρανοήσεις στους Στατιστικούς Ελέγχους Υποθέσεων: Υπέρβαση μέσω της Ανάλυσης Δεδομένων. Τετράδια Ανάλυσης Δεδομένων-Data Analysis Bulletin, 2, 52-64. 5) Μενεξές, Γ. (2007). Μια Δομημένη Προσέγγιση στην Πολυμεταβλητή Στατιστική Ανάλυση Βιολογικών, Περιβαλλοντικών, Κοινωνικών και Οικονομικών Δεδομένων. Στο Φυσικοί Πόροι, Περιβάλλον και Ανάπτυξη (σσ. 519-534). Επιμέλεια: Γ. Αραμπατζής και Σ. Πολύζος. Θεσσαλονίκη: Εκδόσεις Τζιόλα. 6) Μενεξές, Γ. (2013). Οδηγός Ανάλυσης Παραλλακτικότητας Δεδομένων Γεωργικών Πειραμάτων με Στατιστικά Πακέτα. Εκπαιδευτικές Σημειώσεις.
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