Biotechnology and Genomic for Industry and Environment

MARCO ALFO'

Learning goals:
The learning goal of the course is to acquire a basic knowledge of statistical inference.

Knowledge and understanding
At the end of the course, students have a basic knowledge of the theory of point and interval estimation, and of some specific cases of parametric hypotheses testing

Applying knowledge and understanding
At the end of the course, students are able to use the main statistical inference techniques for samples drawn from a normal population

Making judgments
Students ability is stimulated using empirical cases, and the comparison between different approaches to statistical inference

Communication skills
The students' communication skills are enhanced by the critical discussion of the theory of statstical inference

Learning skills
Students with a positive mark have the ability to deal with real empirical cases of limited complexity

At the end of the course, the student knows the basics of statistical analysis applied to experimental data

Basic mathematics knowledge

Introduction
Probability Theory, basics
Random Variables
Probability Models
Sample Statitsics Distributions
Theory of Point Estimation
Theory of Interval Estimation
Testing Statistical Hypotheses, basics
Testing Statistical Hypotheses, power function

Sheldon M. Ross "Probabilità e statistica per l'ingegneria e le scienze", Edizione Apogeo, Milano, 2003, Capitoli 1-8.
Pagano M., Gauvreau K. "Biostatistica", IDELSON-GNOCCHI

Attendance of teaching classes is not compulsory.
The course is structured in frontal theoretical lessons, for a global amount of 48 hours of teaching (6 CFU)
At the end of the course, a self-assessment test will take place, to verify students' level of understanding, and review some key aspects of the program.

Attending the course is not mandatory, but is strongly recommended

The exam test aims at verifying the students' level of understanding with regards to basic topic of parametrical statistical inference, with a view towards comprehension of its basic concepts, and skills acquired in applied perspective. The final mark ranges from 18/30 to 30/30 cum laude. The assessment consists in a written test (lasting approximately two hours) and a viva examination. The aim is at veryfing whether the student has achieved the objectives in terms of understanding and correctly applying main parametric inference methods.

Define the confidence interval for a normal population mean
Define the confidence interval for a normal population variance
Define the rejection region for a simple parametric test

• Exploratory statistics
  • Books: Unit and freuency distributions, summary statistics, dispersion and variability, association and linear dependence


• Probability
  • Books: Basic definition, axioms and frequently used theorems


• Point estimation
  • Books: Basic definitions, choosing and comparing estimators


• Confidence intervals
  • Books: Gaussian distribution, confidence interval for means and variances


• Testing parametric hypotheses
  • Books: Gaussian distributions, testing pared samples means