Forest Biometry I

Course Information
TitleΔΑΣΙΚΗ ΒΙΟΜΕΤΡΙΑ Ι / Forest Biometry I
Code025Υ
FacultyAgriculture, Forestry and Natural Environment
SchoolForestry and Natural Environment
Cycle / Level1st / Undergraduate
Teaching PeriodWinter
CommonNo
StatusInactive
Course ID420000034
Class Information
Academic Year2020 – 2021
Class PeriodWinter
Faculty Instructors
Instructors from Other Categories
Weekly Hours5
Class ID
600175617
Course Type 2016-2020
  • Background
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
  • Face to face
Digital Course Content
Language of Instruction
  • Greek (Instruction, Examination)
Learning Outcomes
After successfully completing the course, students will be able: to design a simple statistical survey, describe a set of data, conclude for the population by random samples and estimate simple statistical models.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Advance free, creative and causative thinking
Course Content (Syllabus)
METHODS OF STATISTICAL ANALYSIS DEFINITION OF STATISTICS. COLLECTION OF STATISTICAL DATA. MEANS OF COLLECTING STATISTICAL DATA. PRESENTATION OF STATISTICAL DATA. PROCESSING OF STATISTICAL DATA. NUMERICAL DESCRIPTION OF THE PROPERTIES OF THE FREQUENCY DISTRIBUTIONS MEASURES OF SCALE. NUMERICAL DESCRIPTION OF FREQUENCY DISTRIBUTIONS BY FREQUENCIES MEASURES OF DISPERSION. NUMERICAL DESCRIPTION OF THE FREQUENCY DISTRIBUTIONS BY FREQUENCY MEASURES OF FORM. POSSIBILITY ELEMENTS. DISTINGUISHED RANDOM VARIABLES. BINOMIAL DISTRIBUTION. POISSON DISTRIBUTION. NORMAL DISTRIBUTION. PRODUCTS THEORETICAL DISTRIBUTIONS. PARAMETER ESTIMATION. POINT ESTIMATION. EVALUATION OF SPACE. THE DISTRIBUTION OF THE POPULATION. ANALYSIS OF VARIANCE. REGRESSION. MULTI-STAGE SAMPLING. MULTIPHASE SAMPLING. SAMPLING IN SEQUENTIAL CASES.
Keywords
Research design, Statistical data description, Statistical conclusion, Model estimation, Sampling
Educational Material Types
  • Notes
  • Slide presentations
  • Interactive excersises
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Laboratory Teaching
  • Use of ICT in Communication with Students
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures39✓
Laboratory Work26✓
Reading Assigment24✓
Written assigments58✓
Exams3
Total150
Student Assessment
Description
Theory and laboratory evaluation (in case of remote examination) Questions through e-learning Short response time Specific questions for each examinee. Theory evaluation (in case of live examination) A final exam (February or September exam) Theory and laboratory questions with expected answer of small development Leading grade 5 based on the evaluation of the answers of the theory. https://elearning.auth.gr/course/view.php?id=10988
Student Assessment methods
  • Written Exam with Short Answer Questions (Summative)
  • Written Assignment (Formative)
  • Written Exam with Problem Solving (Summative)
  • Labortatory Assignment (Formative)
Bibliography
Course Bibliography (Eudoxus)
ΜΑΤΗΣ Κ. ΔΑΣΙΚΗ ΒΙΟΜΕΤΡΙΑ Ι ΣΤΑΤΙΣΤΙΚΗ
Additional bibliography for study
Κολυβά-Μαχαίρα Φ. και Μπόρα-Σέντα Ε., 2013. Στατιστική: Θεωρία-Εφαρμογές. Ζήτη. Θεσσαλονίκη.
Last Update
22-06-2021