ROOM: laboratori informatici (computer lab) ex DIMEG, Via Venezia - Padova
The course is an introduction to statistical methods most frequently used for experimentation in Engineering.
Lectures are planned both in the classroom and in computer lab also for an introduction to the use of the following statistical software:
1. Elements of univariate statistical methods:
Elements of descriptive statistics: frequency, indices of synthesis (position, variability and shape) and graphical representations (histogram, boxplot, scatterplot).
Elements of probability theory: discrete and continuous probability distributions.
Elements of statistical inference: sampling distributions, point and interval estimation, hypothesis testing, One-way ANOVA, Multi-Way ANOVA, Factorial Designs.
Main Reference: Stark, P.B., 1997. SticiGui: Statistics Tools for Internet and Classroom Instruction with a Graphical User Interface
2. Statistical Modelling: Experiments and observational studies, regression, residuals versus error terms, matrix algebra, standard errors, generalized least squares, normal theory of regression, the F-test, path models, inferring causation from regression, response schedules, types of variables, maximum likelihood, probit and logit models, latent variables, the bootstrap for estimating bias and variance.
Attendance is required for at least 2/3 of the lecture hours.
Final evaluation will be based on the discussion of a case study within the individual PhD project.