66106 - Experimental Methodology And Data Analysis

Learning outcomes

At the end of the course the student is able to statistically interpret the relationships between variables and measured parameters. It is able to independently assess the quality and effectiveness of the results obtained, thanks to the appropriate use of tools and operational techniques, supported by experience in the field of statistics. The student will then have acquired the theory of the main basic statistical methods and their applications to case studies, using the programming language R.

 

 

 

Course contents

Section 1. Programming language R Install R and RStudio, Set up a work session, Create basic objects and functions on R. Recognize and create basic structures, objects and functions, Create vectors, matrices, arrays, lists, dataframe farms, Convert objects to R, Use logical operators, Using conditional statements or control structures, Creating functions, Uploading files to R, Manipulating vectors, matrices, datasets. Handle missing values, Handle duplicate data, Manipulate dates, Use some basic statistics functions, Create simple graphs with basic functions, Create graphs with ggplot2.

 

Section 2. Statistical Applications. Basic statistics, probability, probability distributions, descriptive statistics, linear and non-linear models, inferential statistics, hypothesis tests, analysis of variance.

Readings/Bibliography

Random Process Analysis with R (Bittelli, Olmi and Rosa)

Oxford University Press (ISBN: 9780198862512)

Class notes

Teaching methods

The course will be integrated with the programs of the Sensitivity and Vulnerability of the Water-Soil System course (66105) through the statistical analysis of data collected during the practical exercises of the course. The student will be provided with real case study data on which to develop the necessary analytical and statistical skills for a complete development of environmental and territorial studies.

Assessment methods

Written exam. The exam will be divided in two partials. The first one will be given at mid-term (beginning of November) and the second one at the end of the semester. The students who will not take it during the semester will have other sessions with one written exam. 

Teaching tools

During the course, for each topic of data analysis and statistics, real data obtained from different case studies will be provided. The data will be analyzed with R codes written and provided by the teacher.

Links to further information

https://marcobittelli.it/

Office hours

See the website of Marco Bittelli