The course introduces the basic concepts of descriptive Statistics and Probability. Principal topics: distributions and graphics; means, variability, skewness; bivariate distributions, dependence in mean, correlation, simple linear regression. Probability. Random variables, with special emphasis on Binomial, Poisson and Normal.
- G. Cicchitelli, P. D'Urso, M. Minozzo: Statistica: principi e metodi (Terza Edizione) Pearson Italia, Milano, 2017, ISBN 9788891902788 (Chapters 1-7, 9-16).
- Teaching aids released by the teacher through Moodle.
Learning Objectives
The student should learn the basics of descriptive Statistics, understanding the properties of the methods and being able to apply
them to data. Furthermore, the student should know the basics of probability and random variables and should be able to make applications to real cases.
Prerequisites
None
Teaching Methods
lessons in classroom
Type of Assessment
The evaluation is based on three elements:- Written exam, consisting mainly in practical exercises requiring to select an appropriate method, perform calculations (using a pocket calculator) and interpret the results (the two parts of the program are weighted as follows: descriptive statistics 60%, probability 40%; the mark is expressed on the 0-30 scale)- Homeworks executed during the didactic period (optional activity leading to max 2 points to be added to the mark of the written exam)- Oral exam: the student passing the written exam is admitted to the oral exam with starting mark equal to the mark of the written exam plus the points for the homeworks (if any); the oral exam concerns the theory and the interpretation; at the end of the oral exam a final mark is given.
Course program
Introduction. Types of variables. Ratios. Statistical distributions. Graphics. Mode, meadian and analytical means. Variability. Heterogeneity. Skewness and kurtosis. Chebicev inequality. Bivariate distributions. Indexes of association. Variance decomposition and dependence in mean. Covariance and correlation. Simple linear regression. Introduction to probability. Introduction to random variables. Main random variables, with special emphasis on Binomial, Poisson and Normal.