Learning objectives
Course learning objectives are to introduce students to the methods of descriptive and inferential statistics, which have many potential applications in animal husbandry as well as veterinary sciences.
Methods are introduced in an application-oriented manner, taking advantage of computer-based tools for modeling, analysis and visualization of data.
More specifically, the course aims at equipping students with tools expanding their portfolio of professional skills as expert in animal husbandry or veterinary, including proper use of statistics, graphical presentation of data and populations, inference and forecasting of meaningful statistical data.
At the end of the course, the student will be able to make autonomously decisions based on quantitative information, thereby improving the quality level of his/her professional environment. (Dublin descriptors I, II, III).
Moreover, at the end of the course, the student will be able to effectively communicate and interact leveraging upon what has been learned, with prospective customers as well as with colleagues in the profession.
He/she will be able to highlight proper decisions in the frame of animal husbandry and veterinary professional activities using charts, easy-to-understand statistical representations, probability assessment, and confidence intervals.
Finally, the course aims at stimulating in students their critical thinking potential, including the attitude to question consolidated but possibly outdated practices in husbandry, or to challenge what is being learned in class (Dublin descriptors IV and V).
Prerequisites
None
Course unit content
The course comprises three main parts.
Part 1 provides a general view of statistical methods to describe populations, samples and individual subjects. These methods include frequency tables, charts, and meaningful statistical descriptors such as mean, median, and standard deviation. Methods to compare and relate variables are also proposed.
Part 2 provides practical tools and examples of probability theory, enabling its practical application in several animal husbandry and veterinary contexts.
Part 3 introduces estimation techniques of statistical measures over entire populations starting from suitably extracted population samples. Fundamental concepts that will be presented include confidence interval estimation and hypothesis testing, as well as other estimation techniques.
Presentation of all topics is supported by exercises and examples during each lecture as well as in dedicated lectures, based on spreadsheet tools offering statistical functions, such as Microsoft Excel, and other data modeling, analysis and visualization software tools suitable for biostatistics and bioinformatics.
Full programme
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Bibliography
A good textbook on statistics is a valuable resource not only for passing the course exam but also for the profession after graduation.
A broadly used italian textbook on Statistics is the following:
G. Cicchitelli, P. D'Urso, M. Minozzo, "Statistica: principi e metodi", Pearson, 2017. ISBN: 8891902780.
However, many other textbooks, possibly in English if preferred, can serve the purpose.
Students regularly attending classes do not need to rely on the textbook for the purpose of the exam, whereas a textbook provides a comprehensive treatment of the subject an may be needed to students who do not regularily attend classes.
Additional material, including copy of lecture slides, will be available to all students on the Elly web site of the class.
Teaching methods
Lectures in classroom at the Department of Veterinary Sciences.
Assessment methods and criteria
Exam is in two parts: written test followed by interactive / oral test (same day or next working day, if possible).
Written test with multiple quizzes and exercises: max 26 points.
Interactive / oral test with exercises to be solved with Excel or similar tool: max 6 points.
Final mark is the sum of the two individual evaluations, provided that both assessments reach a pass level. The honor mark (30/30 e lode) is assigned if the sum exceeds 30.
Disabled students can receive extra time to cope with the test.
Other information
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