# Applied statistics

 Title Εφαρμοσμένη Στατιστική / Applied statistics Code 13Υ Faculty Agriculture, Forestry and Natural Environment School Forestry and Natural Environment Cycle / Level 1st / Undergraduate Teaching Period Winter Common No Status Active Course ID 600019402

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

Registered students: 99
OrientationAttendance TypeSemesterYearECTS
Compulsory CoursesCompulsory Course114

 Academic Year 2023 – 2024 Class Period Winter Faculty Instructors Maria Diamantopoulou 82hrs Weekly Hours 4 Class ID 600231942

### Class Schedule

 Building Forestry (Finikas) - building b Floor Floor 1 Hall ΑΙΘΟΥΣΑ ΑΣΚΗΣΕΩΝ ΔΑΣΙΚΗΣ ΒΙΟΜΕΤΡΙΑΣ (505) Calendar Monday 16:00 to 18:00 Building Forestry (Finikas) - building b Floor Floor 1 Hall ΑΙΘΟΥΣΑ ΑΣΚΗΣΕΩΝ ΔΑΣΙΚΗΣ ΒΙΟΜΕΤΡΙΑΣ (505) Calendar Monday 18:00 to 20:00 Building Forestry (Finikas) - building d Floor Groundfloor Hall ΑΜΦΙΘΕΑΤΡΟ "ΜΠΑΣΙΩΤΗΣ ΚΩΝΣΤΑΝΤΙΝΟΣ" (ΦΟΙΝΙΚΑΣ/ΑΜΦ. Δ1) (244) Calendar Thursdsay 12:00 to 14:00
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)
• ONLY IN GREEK
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
Keywords
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
Description
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
Lectures260.9
Laboratory Work220.7
Written assigments140.5
Exams30.1
Total1204
Student Assessment
Description
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)
Bibliography
Course Bibliography (Eudoxus)
ΜΑΤΗΣ Κ. ΔΑΣΙΚΗ ΒΙΟΜΕΤΡΙΑ Ι ΣΤΑΤΙΣΤΙΚΗ