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.
Curriculum
Canali
scheda docente
materiale didattico
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.
Programma
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.
Testi Adottati
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.
Bibliografia Di Riferimento
G.Cicchitelli, P.D'Urso, M.Minozzo. Statistica: principi e metodi. Pearson, quarta edizione.Modalità Erogazione
6 lecture hours plus 2 pratical hours per week.Modalità Frequenza
Strongly recommended.Modalità Valutazione
Written exam.
scheda docente
materiale didattico
variables and their measurement, univariate distributions, describing data with tables and graphs, measures of position, variability.
Bivariate descriptive statistics: independence, association, correlation, probability distributions for discrete and continuous variables, sampling distributions
Inference: estimation, hypothesis test, regression
Programma
Descriptive statistics:variables and their measurement, univariate distributions, describing data with tables and graphs, measures of position, variability.
Bivariate descriptive statistics: independence, association, correlation, probability distributions for discrete and continuous variables, sampling distributions
Inference: estimation, hypothesis test, regression
Testi Adottati
A. Agresti, B. Finlay. Statistical methods for the social sciences. Pearson International Edition-4th edition (2009)Modalità Erogazione
The course normally includes classroom lectures. There are 2 hours of weekly exercises for the duration of the course.Modalità Valutazione
The exam consists of a written test, with exercises and theoretical questions. The test is considered passed if the sufficiency is achieved both in the practical and theoretical part. It is not allowed to introduce any formulary and/or book in the exam room. It is allowed to introduce only the tables of probability distributions in the format made available on the course website. A candidate who has successfully passed the written test can request that the mark obtained in the written test be recorded, unless the oral test is requested by the teacher.Canali
scheda docente
materiale didattico
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.
Programma
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.
Testi Adottati
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.
Bibliografia Di Riferimento
G.Cicchitelli, P.D'Urso, M.Minozzo. Statistica: principi e metodi. Pearson, quarta edizione.Modalità Erogazione
6 lecture hours plus 2 pratical hours per week.Modalità Frequenza
Strongly recommended.Modalità Valutazione
Written exam.
scheda docente
materiale didattico
variables and their measurement, univariate distributions, describing data with tables and graphs, measures of position, variability.
Bivariate descriptive statistics: independence, association, correlation, probability distributions for discrete and continuous variables, sampling distributions
Inference: estimation, hypothesis test, regression
Programma
Descriptive statistics:variables and their measurement, univariate distributions, describing data with tables and graphs, measures of position, variability.
Bivariate descriptive statistics: independence, association, correlation, probability distributions for discrete and continuous variables, sampling distributions
Inference: estimation, hypothesis test, regression
Testi Adottati
A. Agresti, B. Finlay. Statistical methods for the social sciences. Pearson International Edition-4th edition (2009)Modalità Erogazione
The course normally includes classroom lectures. There are 2 hours of weekly exercises for the duration of the course.Modalità Valutazione
The exam consists of a written test, with exercises and theoretical questions. The test is considered passed if the sufficiency is achieved both in the practical and theoretical part. It is not allowed to introduce any formulary and/or book in the exam room. It is allowed to introduce only the tables of probability distributions in the format made available on the course website. A candidate who has successfully passed the written test can request that the mark obtained in the written test be recorded, unless the oral test is requested by the teacher.Canali
scheda docente
materiale didattico
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.
Programma
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.
Testi Adottati
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.
Bibliografia Di Riferimento
G.Cicchitelli, P.D'Urso, M.Minozzo. Statistica: principi e metodi. Pearson, quarta edizione.Modalità Erogazione
6 lecture hours plus 2 pratical hours per week.Modalità Frequenza
Strongly recommended.Modalità Valutazione
Written exam.
scheda docente
materiale didattico
variables and their measurement, univariate distributions, describing data with tables and graphs, measures of position, variability.
Bivariate descriptive statistics: independence, association, correlation, probability distributions for discrete and continuous variables, sampling distributions
Inference: estimation, hypothesis test, regression
Programma
Descriptive statistics:variables and their measurement, univariate distributions, describing data with tables and graphs, measures of position, variability.
Bivariate descriptive statistics: independence, association, correlation, probability distributions for discrete and continuous variables, sampling distributions
Inference: estimation, hypothesis test, regression
Testi Adottati
A. Agresti, B. Finlay. Statistical methods for the social sciences. Pearson International Edition-4th edition (2009)Modalità Erogazione
The course normally includes classroom lectures. There are 2 hours of weekly exercises for the duration of the course.Modalità Valutazione
The exam consists of a written test, with exercises and theoretical questions. The test is considered passed if the sufficiency is achieved both in the practical and theoretical part. It is not allowed to introduce any formulary and/or book in the exam room. It is allowed to introduce only the tables of probability distributions in the format made available on the course website. A candidate who has successfully passed the written test can request that the mark obtained in the written test be recorded, unless the oral test is requested by the teacher.Canali
scheda docente
materiale didattico
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.
Programma
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.
Testi Adottati
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.
Bibliografia Di Riferimento
G.Cicchitelli, P.D'Urso, M.Minozzo. Statistica: principi e metodi. Pearson, quarta edizione.Modalità Erogazione
6 lecture hours plus 2 pratical hours per week.Modalità Frequenza
Strongly recommended.Modalità Valutazione
Written exam.
scheda docente
materiale didattico
variables and their measurement, univariate distributions, describing data with tables and graphs, measures of position, variability.
Bivariate descriptive statistics: independence, association, correlation, probability distributions for discrete and continuous variables, sampling distributions
Inference: estimation, hypothesis test, regression
Programma
Descriptive statistics:variables and their measurement, univariate distributions, describing data with tables and graphs, measures of position, variability.
Bivariate descriptive statistics: independence, association, correlation, probability distributions for discrete and continuous variables, sampling distributions
Inference: estimation, hypothesis test, regression
Testi Adottati
A. Agresti, B. Finlay. Statistical methods for the social sciences. Pearson International Edition-4th edition (2009)Modalità Erogazione
The course normally includes classroom lectures. There are 2 hours of weekly exercises for the duration of the course.Modalità Valutazione
The exam consists of a written test, with exercises and theoretical questions. The test is considered passed if the sufficiency is achieved both in the practical and theoretical part. It is not allowed to introduce any formulary and/or book in the exam room. It is allowed to introduce only the tables of probability distributions in the format made available on the course website. A candidate who has successfully passed the written test can request that the mark obtained in the written test be recorded, unless the oral test is requested by the teacher.Canali
scheda docente
materiale didattico
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.
Programma
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.
Testi Adottati
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.
Bibliografia Di Riferimento
G.Cicchitelli, P.D'Urso, M.Minozzo. Statistica: principi e metodi. Pearson, quarta edizione.Modalità Erogazione
6 lecture hours plus 2 pratical hours per week.Modalità Frequenza
Strongly recommended.Modalità Valutazione
Written exam.
scheda docente
materiale didattico
variables and their measurement, univariate distributions, describing data with tables and graphs, measures of position, variability.
Bivariate descriptive statistics: independence, association, correlation, probability distributions for discrete and continuous variables, sampling distributions
Inference: estimation, hypothesis test, regression
Programma
Descriptive statistics:variables and their measurement, univariate distributions, describing data with tables and graphs, measures of position, variability.
Bivariate descriptive statistics: independence, association, correlation, probability distributions for discrete and continuous variables, sampling distributions
Inference: estimation, hypothesis test, regression
Testi Adottati
A. Agresti, B. Finlay. Statistical methods for the social sciences. Pearson International Edition-4th edition (2009)Modalità Erogazione
The course normally includes classroom lectures. There are 2 hours of weekly exercises for the duration of the course.Modalità Valutazione
The exam consists of a written test, with exercises and theoretical questions. The test is considered passed if the sufficiency is achieved both in the practical and theoretical part. It is not allowed to introduce any formulary and/or book in the exam room. It is allowed to introduce only the tables of probability distributions in the format made available on the course website. A candidate who has successfully passed the written test can request that the mark obtained in the written test be recorded, unless the oral test is requested by the teacher.Canali
scheda docente
materiale didattico
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.
Programma
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.
Testi Adottati
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.
Bibliografia Di Riferimento
G.Cicchitelli, P.D'Urso, M.Minozzo. Statistica: principi e metodi. Pearson, quarta edizione.Modalità Erogazione
6 lecture hours plus 2 pratical hours per week.Modalità Frequenza
Strongly recommended.Modalità Valutazione
Written exam.
scheda docente
materiale didattico
variables and their measurement, univariate distributions, describing data with tables and graphs, measures of position, variability.
Bivariate descriptive statistics: independence, association, correlation, probability distributions for discrete and continuous variables, sampling distributions
Inference: estimation, hypothesis test, regression
Programma
Descriptive statistics:variables and their measurement, univariate distributions, describing data with tables and graphs, measures of position, variability.
Bivariate descriptive statistics: independence, association, correlation, probability distributions for discrete and continuous variables, sampling distributions
Inference: estimation, hypothesis test, regression
Testi Adottati
A. Agresti, B. Finlay. Statistical methods for the social sciences. Pearson International Edition-4th edition (2009)Modalità Erogazione
The course normally includes classroom lectures. There are 2 hours of weekly exercises for the duration of the course.Modalità Valutazione
The exam consists of a written test, with exercises and theoretical questions. The test is considered passed if the sufficiency is achieved both in the practical and theoretical part. It is not allowed to introduce any formulary and/or book in the exam room. It is allowed to introduce only the tables of probability distributions in the format made available on the course website. A candidate who has successfully passed the written test can request that the mark obtained in the written test be recorded, unless the oral test is requested by the teacher.