Laboratory of Data Analysis

Code: -
|
CEAR-01/B
Further knowledge useful for job placement: Skills to process and convert data into information useful to solve civil and environmental engineering problems and to support decision-making.

Lesson hours:

24

Practice hours:

-

Propaedeuticities:

none

Credits:

3

Types of examinations:

Exercises discussion and related oral test

Teacher:

Sara Tuozzo

Objectives:

The aim of the laboratory is to deepen the methodological and operational tools to process and organize data concerning civil and environmental engineering variables such as: the climatic characteristics of a given area of intervention, the environmental characteristics of water bodies, the mechanical and hydraulic behaviour of soils in geotechnical applications, the behaviour of transportation systems user. These objectives will be reached by giving to the students all the skills needed to operate with databases and statistical tools using commonly available software, such as ACCESS, SPSS, MATLAB.

Contents:

Data source, finding a sample, minimizing sampling errors. Non-response and missing data. Descriptive statistics: univariate frequencies, descriptive measures for frequency distributions. Basics of Probability: the Normal distribution, sampling distributions, order statistics. Basics of time-series analysis: definition of random process, stationarity. Ergodic processes. Autocovariance function and Power spectral density. The Linear regression model: Fitting a straight line by Least Square, the analysis of variance, significance of regression, the R2 statistics. Checking the straight line fit: lack of fit and pure error, examining residuals.

Teaching materials:

João Moreira, ‎Andre Carvalho, ‎Tomás Horvath, 2018.  A general introduction to data analytics. Wiley

Norman R. Draper, Harry Smith, 1998. Applied Regression Analysis, Wiley.