Course Information
TitleΣΤΑΤΙΣΤΙΚΗ / STATISTICS
CodeΝ006Υ
FacultyAgriculture, Forestry and Natural Environment
SchoolAgriculture
Cycle / Level1st / Undergraduate
Teaching PeriodSpring
CommonYes
StatusActive
Course ID420001750

Programme of Study: PPS Geōponías (2019-sīmera)

Registered students: 365
OrientationAttendance TypeSemesterYearECTS
KORMOSCompulsory Course215

Programme of Study: UPS School of Agriculture (2011-today)

Registered students: 371
OrientationAttendance TypeSemesterYearECTS
KORMOSCompulsory Course215

Class Information
Academic Year2019 – 2020
Class PeriodSpring
Faculty Instructors
Instructors from Other Categories
Weekly Hours4
Total Hours112
Class ID
600142917
Type of the Course
  • Background
  • General Knowledge
  • Skills Development
Course Category
General Foundation
Mode of Delivery
  • Face to face
  • Distance learning
Digital Course Content
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction, Examination)
  • English (Instruction, Examination)
Prerequisites
Required Courses
  • Ν003Υ INFORMATICS
  • Ν005Υ MATHEMATICS
General Prerequisites
Students should be familiar with the use of computers.
Learning Outcomes
Upon completion of this course, students will be able to: 1) Recognize the importance of variation and uncertainty in the world and understand how Statistics can improve decisions when faced with uncertainty. 2) Obtain knowledge of and proficiency with a broad range of statistical concepts and tools useful for statistical applications. 3) Develop critical thinking skills for enabling application of Statistics in Biological sciences.
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
  • Advance free, creative and causative thinking
Course Content (Syllabus)
Scientific research and Statistics. Variability - Variable. Population and sample. Frequency distributions. Measures of central tendency and dispersion. Introduction to Probability Theory -Probability distributions. Confidence intervals. Statistical hypothesis testing. Analysis of Variance (ANOVA). Covariation and correlation. Examples and Applications in Agricultural science.
Keywords
Variability, descriptive statistics, statistical tests
Educational Material Types
  • Notes
  • Slide presentations
  • Video lectures
  • Multimedia
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Communication with Students
  • Use of ICT in Student Assessment
Description
Powerpoint, video, Excel, SPSS, Educational software-tutorial, email.
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures112
Seminars12
Tutorial12
Exams4
Total140
Student Assessment
Description
100% written exams.
Student Assessment methods
  • Written Exam with Multiple Choice Questions (Summative)
  • Written Exam with Short Answer Questions (Summative)
  • Written Exam with Extended Answer Questions (Summative)
  • Written Exam with Problem Solving (Summative)
Bibliography
Course Bibliography (Eudoxus)
Κολυβά-Μαχαίρα, Φ., Μπόρα-Σέντα, Ε. και Μπράτσας Χ.(2018). Στατιστική. Θεωρία και Εφαρμογές Παραδείγματα στην R. Εκδόσεις Ζήτη, Θεσσαλονίκη (Κωδικός Εύδοξος: 77120260). Φωτιάδης, Ν. (1995). "Εισαγωγή στη Στατιστική για βιολογικές επιστήμες". Θεσσαλονίκη: University Studio Preee (Κωδικός Εύδοξος: 17225).
Additional bibliography for study
1) 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. 2) 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.
Last Update
25-11-2020