First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Agricultural Sciences and Veterinary Medicine
ANIMAL SCIENCE AND TECHNOLOGY
Course unit
APPLIED STATISTICS
AGO2042490, A.A. 2017/18

Information concerning the students who enrolled in A.Y. 2016/17

Information on the course unit
Degree course First cycle degree in
ANIMAL SCIENCE AND TECHNOLOGY (Ord. 2013)
IF0325, Degree course structure A.Y. 2013/14, A.Y. 2017/18
N0
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Number of ECTS credits allocated 4.0
Type of assessment Evaluation
Course unit English denomination APPLIED STATISTICS
Website of the academic structure http://www.agrariamedicinaveterinaria.unipd.it/
Department of reference Department of Agronomy, Food, Natural Resources, Animals and the Environment
E-Learning website https://elearning.unipd.it/scuolaamv/course/view.php?idnumber=2017-IF0325-000ZZ-2016-AGO2042490-N0
Mandatory attendance No
Language of instruction Italian
Branch LEGNARO (PD)
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit is available ONLY for students enrolled in ANIMAL SCIENCE AND TECHNOLOGY (Ord. 2013)

Lecturers
Teacher in charge ALESSIO CECCHINATO AGR/17

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Other -- -- 4.0

Mode of delivery (when and how)
Period First semester
Year 2nd Year
Teaching method frontal

Organisation of didactics
Type of hours Credits Hours of
teaching
Hours of
Individual study
Shifts
Practice 2.0 16 34.0 No turn
Lecture 2.0 16 34.0 No turn

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

Examination board
Board From To Members of the board
7 Commissione a.a. 2017/18 01/12/2017 30/11/2018 CECCHINATO ALESSIO (Presidente)
MANTOVANI ROBERTO (Membro Effettivo)
TAGLIAPIETRA FRANCO (Supplente)
6 Commissione a.a. 2016/17 01/12/2016 30/11/2017 CECCHINATO ALESSIO (Presidente)
MANTOVANI ROBERTO (Membro Effettivo)
TAGLIAPIETRA FRANCO (Supplente)

Syllabus
Prerequisites: None.
Target skills and knowledge: To introduce the student of the Degree in Animal Science and Technology to the main statistical techniques in application contexts where it arises spontaneously making their use. The course will focus both on the theoretical foundations and in their proper application to real problems.
The aim of the course is to provide the tools necessary to:
- Know how to manage a set of data,
- Represent a set of data in an effective way,
- Being able to read a data set in a critical way,
- Make choices,
- Be able to plan and carry out simple experiments.
Examination methods: Written test on theory and exercises.
Assessment criteria: The preparation of the student will be evaluated based on the degree of knowledge of the theoretical principles and applications of statistical methods presented within the teaching.
Course unit contents: Introduction to statistics: descriptive statistics and inferential statistics. The concepts of population, sample, statistical unit.
Descriptive statistics: types of variables, indicators of central tendency and variability or dispersion, the concept of frequency, graphic representations of data, correlation and contingency tables.
The main elements of probability and probability distributions. The Gaussian or normal probability distribution.
From descriptive statistics to inferential statistics: the concept of replication and simple random sampling.
The confidence intervals and hypothesis testing. One sample tests, two sample tests and tests for paired data.
The one-way analysis of variance for comparing C> 2 populations.
The hypothesis testing for categorical data using the chi-square test.
The simple linear regression.
Planned learning activities and teaching methods: Lectures, exercises and tutorials.
Additional notes about suggested reading: Slide and material provided by the teacher and textbook.
The course material is available at the link: https://elearning.unipd.it/scuolaamv/
Textbooks (and optional supplementary readings)
  • Levine, D.M., Krehbiel T.C., Berenson M.L., Statistica. Milano: Pearson, 2010. Cerca nel catalogo