Learning outcomes of the course unit
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.
Course contents summary
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.
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.
Soliani L., (2015). Statistica di Base. Piccin (PD).
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.