Biostatistics and Bioinformatics
A.Y. 2022/2023
Learning objectives
The objective of the course is to teach the student the basic knowledge of biostatistics and bioinformatics. Such knowledge will be fundamental for a proper experimental design and data analysis, as well as for statistical interpretation and evaluation of experimental results.
Expected learning outcomes
At the end of the course, the students will acquire a good knowledge about the main statistical tests and models that are used in biology and animal science and their will be able to select the proper ones for the experiments and analysis in the field of interest.
Lesson period: Second semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Lesson period
Second semester
Course syllabus
Lectures (32 hours):
- Data, variables, and their representation and description (3 hours);
- Probability: random variables and distributions (3 hours);
- Correlation between variables, linear and non-linear regression (3 hours);
- Test for hypothesis, type I and type II errors, statistical power of a test (3 hours);
- Parametric tests: different types of t-tests (3 hours);
- Parametric tests: analysis of variance, levels and factors, inter- and intra-group variability, F-test (3 hours);
- Post hoc-comparisons, different types of corrections for multiple hypothesis testing, Bonferroni and False Discovery Rate methods (3 hours);
- Non-parametric equivalents of t-tests (3 hours);
- Non-parametric equivalents of ANOVA (3 hours) ;
- Goodness of fit tests, tests for proportions (3 hours);
- Survival analysis (2 hours).
Practicals (32 hours):
Application of the topics explained during lectures to real world datasets using the SPSS software.
- Data, variables, and their representation and description (3 hours);
- Probability: random variables and distributions (3 hours);
- Correlation between variables, linear and non-linear regression (3 hours);
- Test for hypothesis, type I and type II errors, statistical power of a test (3 hours);
- Parametric tests: different types of t-tests (3 hours);
- Parametric tests: analysis of variance, levels and factors, inter- and intra-group variability, F-test (3 hours);
- Post hoc-comparisons, different types of corrections for multiple hypothesis testing, Bonferroni and False Discovery Rate methods (3 hours);
- Non-parametric equivalents of t-tests (3 hours);
- Non-parametric equivalents of ANOVA (3 hours) ;
- Goodness of fit tests, tests for proportions (3 hours);
- Survival analysis (2 hours).
Practicals (32 hours):
Application of the topics explained during lectures to real world datasets using the SPSS software.
Prerequisites for admission
No pre-required knowledge is necessary for this course.
Teaching methods
The course consists of both theoretical lectures and practicals using the SPSS software.
Teaching Resources
Slides used for the lectures and the material for the practicals will be shared through the Ariel portal.
The following is a text that can be used to further explore the topic, but it is optional: "Biostatistics for animal science: an introductory text.", M. Kaps & W. Lamberson, CABI Editors.
The following is a text that can be used to further explore the topic, but it is optional: "Biostatistics for animal science: an introductory text.", M. Kaps & W. Lamberson, CABI Editors.
Assessment methods and Criteria
The exam is made of two parts: a group assignment (2-3 people per group), which will be given in the last week of the course, and a mandatory oral exam.
ING-INF/06 - ELECTRONIC AND INFORMATICS BIOENGINEERING - University credits: 6
Practicals: 32 hours
Lessons: 32 hours
Lessons: 32 hours
Professors:
Laureanti Rita, Reali Pierluigi