Statistics is a compulsory course aimed at introducing the basic techniques for the analysis of statistical data. Topics taught include displaying and describing data, basic probability theory and statistical inference. Attention will be focused on applications to business and economics.
At the end of the course, the student will have:
- become familiar with the main concepts and methods of descriptive statistical analysis, probability and inference;
- acquired a theoretical understanding of statistical techniques and an appropriate critical sense in choosing the most suitable indicators and techniques for the analysis of data sets with specific characteristics;
- developed the ability to analyse real data sets by choosing the most appropriate technique, applying it and interpreting the results.
At the end of the course, the student will have:
- become familiar with the main concepts and methods of descriptive statistical analysis, probability and inference;
- acquired a theoretical understanding of statistical techniques and an appropriate critical sense in choosing the most suitable indicators and techniques for the analysis of data sets with specific characteristics;
- developed the ability to analyse real data sets by choosing the most appropriate technique, applying it and interpreting the results.
Curriculum
Canali
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.
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.
Reference Bibliography
G.Cicchitelli, P.D'Urso, M.Minozzo. Statistica: principi e metodi. Pearson, fourth edition.Attendance
Strongly recommended.Type of evaluation
Written exam 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.
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.
Reference Bibliography
G.Cicchitelli, P.D'Urso, M.Minozzo. Statistica: principi e metodi. Pearson, fourth edition.Attendance
Strongly recommended.Type of evaluation
Written exam.Canali
Mutuazione: 21210113 STATISTICA in Economia e gestione aziendale L-18 R A - C
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.
Mutuazione: 21210113 STATISTICA in Economia e gestione aziendale L-18 R D - K 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.
Reference Bibliography
G.Cicchitelli, P.D'Urso, M.Minozzo. Statistica: principi e metodi. Pearson, fourth edition.Attendance
Strongly recommended.Type of evaluation
Written examMutuazione: 21210113 STATISTICA in Economia e gestione aziendale L-18 R L - P
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.
Mutuazione: 21210113 STATISTICA in Economia e gestione aziendale L-18 R Q - Z 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.
Reference Bibliography
G.Cicchitelli, P.D'Urso, M.Minozzo. Statistica: principi e metodi. Pearson, fourth edition.Attendance
Strongly recommended.Type of evaluation
Written exam.Canali
Mutuazione: 21210113 STATISTICA in Economia e gestione aziendale L-18 R A - C
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.
Mutuazione: 21210113 STATISTICA in Economia e gestione aziendale L-18 R D - K 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.
Reference Bibliography
G.Cicchitelli, P.D'Urso, M.Minozzo. Statistica: principi e metodi. Pearson, fourth edition.Attendance
Strongly recommended.Type of evaluation
Written examMutuazione: 21210113 STATISTICA in Economia e gestione aziendale L-18 R L - P
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.
Mutuazione: 21210113 STATISTICA in Economia e gestione aziendale L-18 R Q - Z 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.
Reference Bibliography
G.Cicchitelli, P.D'Urso, M.Minozzo. Statistica: principi e metodi. Pearson, fourth edition.Attendance
Strongly recommended.Type of evaluation
Written exam.Canali
Mutuazione: 21210113 STATISTICA in Economia e gestione aziendale L-18 R A - C
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.
Mutuazione: 21210113 STATISTICA in Economia e gestione aziendale L-18 R D - K 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.
Reference Bibliography
G.Cicchitelli, P.D'Urso, M.Minozzo. Statistica: principi e metodi. Pearson, fourth edition.Attendance
Strongly recommended.Type of evaluation
Written examMutuazione: 21210113 STATISTICA in Economia e gestione aziendale L-18 R L - P
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.
Mutuazione: 21210113 STATISTICA in Economia e gestione aziendale L-18 R Q - Z 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.
Reference Bibliography
G.Cicchitelli, P.D'Urso, M.Minozzo. Statistica: principi e metodi. Pearson, fourth edition.Attendance
Strongly recommended.Type of evaluation
Written exam.