The course aims at providing students with specific competences in sampling tecniques and statistical data analysis. Particular relevance is given to probability and inference, as the course means to provide students with the necessary tools for supporting decisional processes through the management of data bases and the use of statistical models.
teacher profile teaching materials
Descriptive statistics: graphical summaries of data, measuring the center of quantitative data (mode, median, mean), measuring the variability of quantitative data (standard deviation, variance), simmetry of a distribution (Fisher coefficient), the association between two variables (chi-square), the association between two quantitative variables (covariance, correlation coefficient).
Probability: probability of events (probability of the complement of an event, of the union and intersection of two events, conditional probability, independent events, Bayes theorem), discrete and continuous random variables (the Bernoully r.v., the Binomial r.v., the Poisson r.v., the Normal r.v., the Student t r.v., che Chi-square r.v.).
Inferential statistics: sample versus population, sampling distributions, point and interval estimates of population parameters, confidence intervals for a population mean and a proportion, significance tests about hypotheses on a population mean and a proportion, p-values.
Regression analysis: the regression line, ordinary least squares, describing the strength of the association, nonlinear regression models, confidence intervals and tests on the parameters of the regression line, prediction.
Chap. 1 (excluding 1.11), Chap. 2 (excluding 2.4, 2.5), Chap. 3 (excluding 3.4, 3.5, 3.6), Chap. 4 (excluding 4.3, 4.4, 4.5, 4.6, 4.15), Chap. 5 (excluding 5.3, 5.6, 5.7, 5.8), Chap. 6 (excluding 6.3), Chap. 9 (excluding 9.3), Chap. 10, Chap. 11 (excluding 11.2.1), Chap. 12, Chap. 13, Chap. 14 (excluding 14.2, 14.6, 14.7),Chap. 17 (excluding 17.6), Chap.18 (excluding 18.3, 18.4), Chap. 19 (excluding 19.5), Chap. 20 (excluding 20.6, 20.7), Chap. 22 (excluding 22.2.2), Chap. 23.
A collection of exercises by the teacher is available to students on Moodle.
Fruizione: 21210410 Statistica in Economia L-33 A - L CONIGLIANI CATERINA
Programme
An introduction to the fundamental ideas of statistics. Topics include:Descriptive statistics: graphical summaries of data, measuring the center of quantitative data (mode, median, mean), measuring the variability of quantitative data (standard deviation, variance), simmetry of a distribution (Fisher coefficient), the association between two variables (chi-square), the association between two quantitative variables (covariance, correlation coefficient).
Probability: probability of events (probability of the complement of an event, of the union and intersection of two events, conditional probability, independent events, Bayes theorem), discrete and continuous random variables (the Bernoully r.v., the Binomial r.v., the Poisson r.v., the Normal r.v., the Student t r.v., che Chi-square r.v.).
Inferential statistics: sample versus population, sampling distributions, point and interval estimates of population parameters, confidence intervals for a population mean and a proportion, significance tests about hypotheses on a population mean and a proportion, p-values.
Regression analysis: the regression line, ordinary least squares, describing the strength of the association, nonlinear regression models, confidence intervals and tests on the parameters of the regression line, prediction.
Core Documentation
G.Cicchitelli, P.D'Urso, M.Minozzo. Statistica: principi e metodi. Pearson, fourth edition:Chap. 1 (excluding 1.11), Chap. 2 (excluding 2.4, 2.5), Chap. 3 (excluding 3.4, 3.5, 3.6), Chap. 4 (excluding 4.3, 4.4, 4.5, 4.6, 4.15), Chap. 5 (excluding 5.3, 5.6, 5.7, 5.8), Chap. 6 (excluding 6.3), Chap. 9 (excluding 9.3), Chap. 10, Chap. 11 (excluding 11.2.1), Chap. 12, Chap. 13, Chap. 14 (excluding 14.2, 14.6, 14.7),Chap. 17 (excluding 17.6), Chap.18 (excluding 18.3, 18.4), Chap. 19 (excluding 19.5), Chap. 20 (excluding 20.6, 20.7), Chap. 22 (excluding 22.2.2), Chap. 23.
A collection of exercises by the teacher is available to students on Moodle.
Type of delivery of the course
6 lecture hours plus 2 pratical hours per week.Attendance
Strongly recommended.Type of evaluation
Written exam.