Applied statistics

Course Information
TitleΕφαρμοσμένη Στατιστική / Applied statistics
FacultyAgriculture, Forestry and Natural Environment
SchoolForestry and Natural Environment
Cycle / Level1st / Undergraduate
Teaching PeriodWinter
Course ID600019402

Programme of Study: PPS Tmīmatos Dasologías kai Fysikoý Perivállontos (2020-sīmera)

Registered students: 99
OrientationAttendance TypeSemesterYearECTS
Compulsory CoursesCompulsory Course114

Class Information
Academic Year2023 – 2024
Class PeriodWinter
Faculty Instructors
Weekly Hours4
Class ID
Course Type 2021
General Foundation
Course Type 2016-2020
  • Background
Course Type 2011-2015
General Foundation
Mode of Delivery
  • Face to face
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
  • Work autonomously
  • Advance free, creative and causative thinking
Course Content (Syllabus)
Definition of statistics, population, sample, categories of variables, collection of statistical data, presentation of statistical data, frequency tables, charts, processing of statistical data, properties of frequency distributions, measures of central tendency, mean, median, type, relationship between mean, median and type, quartiles and percentiles, numerical description of properties of distributions by frequency, range, standard deviation, variance or dispersion, properties of variation , standard deviation, measures of shape, measures of asymmetry or skewness, measures of kurtosis, probability data, random experiments, random events or contingencies – sample space, definition of probability, random variable, expected value, discrete random distributions (bernoulli, binomial distribution, roisson, hypergeometric distribution), normal distribution, standard normal distribution, generating theoretical distributions (x2 distribution, student's distribution or t distribution, f distribution, parameter estimation, point estimation, interval estimation, hypothesis testing, categorical data analysis, goodness-of-fit test, independence test, rxc correlation matrices, analysis of variance, multiple comparisons, least significant difference, correlation, regression, non-parametric tests, Kolmogorov test - Smirnov one-sample goodness-of-fit test, one-sample flow or permutation test, two-sample non-parametric tests, Mann-Whitney U-test. Homogeneity test of two independent samples, Wilcoxon test. Homogeneity test for two dependent samples, Kruskal-Wallis test. Anova, Spearman's rank correlation coefficient
Statistical Analysis, Description of Statistical Data, Modeling, Sampling
Educational Material Types
  • 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
  • Use of ICT in Student Assessment
During the teaching and laboratory training, a slide show with relevant content, photos and anything else that is deemed necessary is used in order for the trainees to have a complete picture of the content of the lectures. There is also training in the use of software (SPSS and EXCEL) in order for students to be able to solve dendrometry problems that are called to learn to solve
Course Organization
Laboratory Work220.7
Reading Assigment551.8
Written assigments140.5
Student Assessment
Theory and laboratory evaluation. Theory assessment: Through written exams with multiple choice questions, short development and solving exercises. Laboratory evaluation: Through the delivery of written work using statistical and computer packages and the evaluation of students through questions on it. Grading: Laboratory evaluation with excellent performance of 20/100 units. Theory evaluation with excellent performance of 80/100 units. Leading grade 50/100, cumulatively.
Student Assessment methods
  • Written Exam with Multiple Choice Questions (Summative)
  • Written Exam with Short Answer Questions (Summative)
  • Written Exam with Problem Solving (Formative, Summative)
  • Labortatory Assignment (Formative, Summative)
Course Bibliography (Eudoxus)
Additional bibliography for study
Avery, T.E. and Burkhart, H.E. 2001. Forest Measurements. 5th edition: McGraw-Hill Publishing Company Διαμαντοπούλου Μ.Ι., 1997. Σημειώσεις Βιομετρίας-Βιοστατιστικής. Θεσσαλονίκη. 156 σελ. Διαμαντοπούλου Μ.Ι., 1999. Σημειώσεις εργαστηρίου Σχεδιασμού Πειραμάτων. Επίλυση ασκήσεων του μαθήματος του Σχεδιασμού Πειραμάτων με τη χρήση του στατιστικού πακέτου SPSS. Θεσσαλονίκη, 101 σελ. Διαμαντοπούλου Μ.Ι., 2002. Σημειώσεις Δασικής Βιομετρίας – Δενδρομετρίας Ι. Θεωρία – Εργαστήριο. Θεσσαλονίκη. 186 σελ. Fransis, A., 1990. Advanced Level Statistics. An Integrated Course. Second Edition.The Bath Press. Avon. Great Britain. Κιόχος, Π.Α., 1993. Στατιστική. Εκδόσεις Ιnterbooks. Αθήνα. 761 σελ. Κολυβά-Μαχαίρα Φ. και Μπόρα-Σέντα Ε., 2013. Στατιστική: Θεωρία-Εφαρμογές. Ζήτη. Θεσσαλονίκη. Κουνιάς, Σ.Γ., Κολυβά - Μαχαίρα, Φ., Μπαγιάτης, Κ. και Μπόρα-Σέντα, Ε., 1985. Εισαγωγή στη Στατιστική. Θεσσαλονίκη. 417 σελ. Μάτης Κ., 2003. Δασική Βιομετρία Ι. Στατιστική, Εκδόσεις Πήγασος, 598 σελ. Neter, J., Wasserman, W. and Kunter, M.H., 1990 Applied Linear Statistical Models. 3rd Edition. Richard D. Irwin, Inc. Homewood, Illinois 60430. 1181p. Παπαδημητρίου, Ι., 1990. Στατιστική. Τεύχος Ι. Περιγραφική Στατιστική. Εκδόσεις Παρατηρητής. Θεσσαλονίκη. 470 σελ. Ρούσσας, Γ. Γ., 1992. Θεωρία των πιθανοτήτων. Επιμέλεια - Μετάφραση Δημήτριος Ιωαννίδης. Εκδόσεις Ζήτη. Θεσσαλονίκη. 313 σελ. Σταματέλος, Γ., 1997. Σημειώσεις Πιθανοτήτων Στατιστικής Ι με Εφαρμογές στην Τεχνολογία. Θεσσαλονίκη. 149 σελ. The Empirical Rule and Chebyshev’s Theorem. (2021, January 11). Retrieved June 9, 2021, from
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