First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Agricultural Sciences and Veterinary Medicine
SUSTAINABLE AGRICULTURE
Course unit
ADVANCED STATISTICS
AVP5073737, A.A. 2017/18

Information concerning the students who enrolled in A.Y. 2017/18

Information on the course unit
Degree course Second cycle degree in
SUSTAINABLE AGRICULTURE
AV2293, Degree course structure A.Y. 2016/17, A.Y. 2017/18
N0
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Degree course track SUSTAINABLE AGRICULTURE [001LE]
Number of ECTS credits allocated 8.0
Type of assessment Mark
Course unit English denomination ADVANCED STATISTICS
Website of the academic structure http://www.agrariamedicinaveterinaria.unipd.it
Department of reference Department of Agronomy, Food, Natural Resources, Animals and the Environment
Mandatory attendance No
Language of instruction English
Branch LEGNARO (PD)

Lecturers
Teacher in charge ANTONIO BERTI AGR/02

Mutuated
Course unit code Course unit name Teacher in charge Degree course code
AVP5073737 ADVANCED STATISTICS ANTONIO BERTI AV2293

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Educational activities in elective or integrative disciplines AGR/02 Agronomy and Herbaceous Cultivation 8.0

Mode of delivery (when and how)
Period First semester
Year 1st Year
Teaching method frontal

Organisation of didactics
Type of hours Credits Hours of
teaching
Hours of
Individual study
Shifts
Practice 3.0 24 51.0 No turn
Lecture 5.0 40 85.0 No turn

Calendar
Start of activities 02/10/2017
End of activities 19/01/2018

Syllabus
Prerequisites: Basic statistical knowledge (frequency distributions, representation of data, parametric test for mean comparison, linear regression)
Target skills and knowledge: The class is aimed to give to students the knowledge on planning and analysis of agricultural experiments and for environmental monitoring.
The class will focus on the selection of experimental layouts, on the analysis of continuous and discrete variables, the assumptions of parametric tests and the applicability of non parametric approaches.
Examination methods: The final evaluation will be by means of written exam and by means of the preparation and exposition of a group work
Assessment criteria: The evaluation of the student will be based on the comprehension of the addressed topics and on the base of the concepts and methodologies learnt during the class. The ability of the student of using such aspects in an independent way will also be taken into account.
Course unit contents: Planning and analysis of complex experiments, factorial ANOVA and concept of interaction between factors
- Variability of measurements: type of data, constraints in the application of factors
- Time and space variability
- Review of ANOVA concept and factorial ANOVA
- Interaction between factors, examples of first- and higher- order interactions
- Experimental plans: completely randomised, randomized blocks, latin squares, split-plot and split-block
- Assumptions of ANOVA and test of assumptions, transformation of data
- Non parametric tests for between groups comparisons and for relationship between variables. Analysis of categorical data
- Analysis of continuous variables, linear and non linear models, multiple linear regression, evaluation of fitting of non-liner models
- Comparison between different models, measure of the relative quality of a statistical model
Planned learning activities and teaching methods: The course will be done in classroom with theoretical lectures and practical exercises in computer room
Additional notes about suggested reading: The material used for the course will be made available to students through the Moodle platform of the School at
https://elearning.unipd.it/scuolaamv/login/index.php
Textbooks (and optional supplementary readings)