STATISTICS
cod. 1000666

Academic year 2018/19
3° year of course - First semester
Professor
Antonio BODINI
Academic discipline
Statistica (SECS-S/01)
Field
Attività formative affini o integrative
Type of training activity
Related/supplementary
48 hours
of face-to-face activities
6 credits
hub: PARMA
course unit
in ITALIAN

Learning objectives

Learning objectives consist in reaching a good level in terms of knowledge and skills, which are seen in a continuous interaction during the class work. Of particular importance, to this end, is the capability to handle data and information
selecting the most appropriate way of treating them to solve descriptive as well as management problems in the fields of natural and environmental sciences.
Independence of judgment is vital for a discipline whose pillar is to guide the students in process of deciding which data treatment is the most appropriate to answer practical questions.

Prerequisites

- - -

Course unit content

The aim of the course is to introduce the students to the comprehension of the fundamentals of data analysis for the natural and environmental sciences. The theoretical foundations for data collection, their description and their manipulation in the problem-solving framework are significant aspects of the course.

Full programme

1. Descritpive statistics (univariate distributions).
2. Probability and main theoretical distributions.
3. Frequencies and proportions.
4. Statistical significance and hypothesis testing.
5. Comparing two means: the Student's t test.
6. Analysis of the variance.
7. Correlation.
8. Regression.

Bibliography

Soliani L., (2015). Statistica di Base. Piccin (PD).

Teaching methods

Lecturing and exercises. The exercises will be organized within a problem-solving approach. In this framework the students will be asked to choose the information needed, decide the sample size and select the most appropriate test to apply.

Assessment methods and criteria

An oral final examination will be structures in two parts: one dedicated to assess the level of knowledge about data analysis techniques and the second to assess the skills through the solution of a management exercise.

Other information

- - -

2030 agenda goals for sustainable development

- - -