First cycle degree courses Second cycledegree courses Single cycledegree courses School of Economics and Political Science ECONOMIC LAW
Course unit
STATISTICS
SP07107824, A.A. 2014/15

Information concerning the students who enrolled in A.Y. 2014/15

Information on the course unit
Degree course Number of ECTS credits allocated First cycle degree in ECONOMIC LAW SP1841, Degree course structure A.Y. 2011/12, A.Y. 2014/15 bring this pagewith you 9.0 Mark STATISTICS Department of Political Science, Law, and International Studies No Italian ROVIGO The Course unit can be attended under the option Single Course unit attendance The Course unit can be chosen as Optional Course unit

Lecturers
 Teacher in charge CINZIA MORTARINO SECS-S/01

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Core courses SECS-S/01 Statistics 9.0

Course unit organization
Period First semester 1st Year frontal

Type of hours Credits Teaching
hours
Hours of
Individual study
Shifts
Lecture 9.0 65 160.0 No turn

Calendar
Start of activities 22/09/2014 24/01/2015 2019/20 Reg.2018 course timetable

Examination board
Examination board not defined

Syllabus
 Target skills and knowledge: Ability in an economic or business problem setting requiring a statistical approach. Application of marginal and relational techniques aimed at recognising forms of dependence, allowing prediction and related corrective actions. Detection and control of significant dominant factors in typical economic or managerial contexts Examination methods: Written exam. Course unit contents: 1). The statistical model: general aspects. Introduction to statistics. Data collection, types of statistical variables. Automatic and manual counting. The frequency distribution. 2). Qualitative variables a) Univariate distributions: Location of a distribution, mode, median. Variability and its measure, Gini and Shannon indexes. b) Bivariate distributions: Joint, marginal and conditional. Stochastic independence. Association: Mortara and Pearson indexes. Conditional, residual and total entropy; entropic dependence indexes. 3). Quantitative variables a) The univariate case. Frequency distributions, density, frequency. Measures of location: mode, median, quantiles. Power means. Dispersion and global variability indicators: mean absolute deviation, mean differences, standard deviation, variance. Box-and-whiskers diagrams. Variability comparisons. b) The bivariate case. Distributions: bivariate joint, marginal and conditional. Stochastic independence. Conditional means and variances, regression function. Mean independence. Correlation ratio. Covariance, correlation and linear constraints. Least squares method, polynomial regression. Goodness-of-fit indexes, lack-of-fit. Residual analysis. c) The multivariate case. Multiple regression analysis. Partial correlation. Selection of explanatory variables in a linear model, partial correlation. Stepwise regression: software and operational aspects of the regression model. Textbooks (and optional supplementary readings) MORTARINO, C., Statistica. Esercizi svolti, 2a ed.. Padova: CLEUP, 2007. Capp. 1-7 e cap. 12 GUSEO, R., Statistica, 3a ed.. Padova: CEDAM, 2006. Capp. 1-6