Teaching - Università Roma Tre

STATISTICS (objectives)

Code

21210113

Language

ITA

Type of certificate

Profit certificate

Credits

10

Scientific Disciplinary Sector Code

SECS-S/01

Contact Hours

66

Type of Activity

Core compulsory activities

Group: A - D

Teacher	PETRARCA FRANCESCA (syllabus) 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 (reference books) A. Agresti, B. Finlay Statistical methods for the social sciences Pearson International Edition - 4th edition 2009 Introductory statistics for business and economics Wonnacot - Wonnacot John Wiley&sons; International 2 revised ed.
Dates of beginning and end of teaching activities	From 25/02/2020 to 31/05/2020
Delivery mode	Traditional
Attendance	not mandatory
Evaluation methods	Written test

Group: E - O

Teacher	MORTERA JULIA (syllabus) Course Topics This graduate level course covers the following topics: An overview of statistics Data description: scales of measurement, how to describe data graphically for categorical data (pie chart, bar chart) and graphs for quantitative variables (histogram, pie chart and time plot) How to describe data by summary statistics: measures of central tendency and variability How to create a box plot How probability and probability distributions are involved in statistics How binomial distributions are involved in statistics The role that normal distributions play in statistics Simple random sampling and sampling distribution of sample mean, central limit theorem, normal approximation to the binomial Differentiation between a population and a sample, how to use a statistic to estimate a population parameter, confidence interval and its interpretation, inferences of population proportion, margin of error and sample size computation Confidence interval for population mean, Sample size needed for estimating the population mean with a specified confidence level and specified width of the interval Hypothesis testing: in terms of how to set up Null and Alternative hypotheses, understanding Type I and Type II errors, performing a statistical test for the population mean How to compute power of a test and choosing the sample size for testing population mean p-value, how to compute it and how to use it Inferences about μ with σ unknown: the t-distribution and the assumptions required to check in order to use it How to compare the mean of two populations for independent samples: using pooled variances t-test versus separate variances t-test How to compare the mean of two populations for paired data How to compare two population proportions Using contingency table and the Chi-square test of independence Understanding concepts related to linear regression models including, least squares method, correlation, inferences about the parameters in the linear regression model (reference books) Introductory Statistics for Business and Economics by Thomas H. Wonnacott and Ronald J. Wonnacott John Wiley & Sons Inc; International 2 Revised ed Further lecture notes are available at http://host.uniroma3.it/facolta/economia/economia.asp?contenuto=insegnamento&id=488 Solutions of some exercises with references to theory and exams can be found at website http://host.uniroma3.it/docenti/mortera/statisticaNNO/statisticaNNO.htm
Dates of beginning and end of teaching activities	From 25/02/2020 to 31/05/2020
Delivery mode	Traditional
Attendance	not mandatory
Evaluation methods	Written test Oral exam

Teacher	MORTERA JULIA (syllabus) Course Topics This graduate level course covers the following topics: An overview of statistics Data description: scales of measurement, how to describe data graphically for categorical data (pie chart, bar chart) and graphs for quantitative variables (histogram, pie chart and time plot) How to describe data by summary statistics: measures of central tendency and variability How to create a box plot How probability and probability distributions are involved in statistics How binomial distributions are involved in statistics The role that normal distributions play in statistics Simple random sampling and sampling distribution of sample mean, central limit theorem, normal approximation to the binomial Differentiation between a population and a sample, how to use a statistic to estimate a population parameter, confidence interval and its interpretation, inferences of population proportion, margin of error and sample size computation Confidence interval for population mean, Sample size needed for estimating the population mean with a specified confidence level and specified width of the interval Hypothesis testing: in terms of how to set up Null and Alternative hypotheses, understanding Type I and Type II errors, performing a statistical test for the population mean How to compute power of a test and choosing the sample size for testing population mean p-value, how to compute it and how to use it Inferences about μ with σ unknown: the t-distribution and the assumptions required to check in order to use it How to compare the mean of two populations for independent samples: using pooled variances t-test versus separate variances t-test How to compare the mean of two populations for paired data How to compare two population proportions Using contingency table and the Chi-square test of independence Understanding concepts related to linear regression models including, least squares method, correlation, inferences about the parameters in the linear regression model (reference books) Introductory Statistics for Business and Economics by Thomas H. Wonnacott and Ronald J. Wonnacott John Wiley & Sons Inc; International 2 Revised ed Further lecture notes are available at http://host.uniroma3.it/facolta/economia/economia.asp?contenuto=insegnamento&id=488 Solutions of some exercises with references to theory and exams can be found at website http://host.uniroma3.it/docenti/mortera/statisticaNNO/statisticaNNO.htm
Dates of beginning and end of teaching activities	From 25/02/2020 to 31/05/2020
Delivery mode	Traditional
Attendance	not mandatory
Evaluation methods	Written test Oral exam

Group: P - Z

Teacher	VICARD PAOLA (syllabus) This graduate level course covers the following topics: An overview of statistics Data description: scales of measurement, how to describe data graphically for categorical data (pie chart, bar chart) and graphs for quantitative variables (histogram, pie chart) How to describe data by summary statistics: measures of central tendency, variability and skewness. How to create a box plot How probability and probability distributions are involved in statistics How binomial distributions are involved in statistics The role that normal distributions play in statistics Simple random sampling and sampling distribution of sample mean, central limit theorem, normal approximation to the binomial Differentiation between a population and a sample, how to use a statistic to estimate a population parameter, confidence interval and its interpretation, inferences of population mean and proportion Confidence interval for population mean, Sample size needed for estimating the population mean with a specified confidence level and specified width of the interval Hypothesis testing: in terms of how to set up Null and Alternative hypotheses, understanding Type I and Type II errors, performing a statistical test for the population mean p-value, how to compute it and how to use it Inferences about μ with σ unknown: the t-distribution and the assumptions required to check in order to use it How to compare the mean of two populations for independent samples: using pooled variances t-test versus separate variances t-test How to compare the mean of two populations for paired data How to compare two population proportions Using contingency table and the Chi-square test of independence Understanding concepts related to linear regression models including, least squares method, correlation, inferences about the parameters in the linear regression model (reference books) The course the course is taught in Italian so textbooks are in Italian: - G. Cicchitelli, Statsitica: Principi e Metodi, Pearson Education, 3/Eds - Sebastiani M. R. (2015) “Esercitazioni di statistica”. Esculapio Editore, 3° edizione. For English speaking students a textbook is: Introductory Statistics for Business and Economics by Thomas H. Wonnacott and Ronald J. Wonnacott John Wiley & Sons Inc; International 2 Revised ed Notes and handout (in Italian) are available at the web page of the course.
Dates of beginning and end of teaching activities	From 25/02/2020 to 31/05/2020
Delivery mode	Traditional At a distance
Attendance	not mandatory
Evaluation methods	Written test Oral exam

Teacher	VICARD PAOLA (syllabus) This graduate level course covers the following topics: An overview of statistics Data description: scales of measurement, how to describe data graphically for categorical data (pie chart, bar chart) and graphs for quantitative variables (histogram, pie chart) How to describe data by summary statistics: measures of central tendency, variability and skewness. How to create a box plot How probability and probability distributions are involved in statistics How binomial distributions are involved in statistics The role that normal distributions play in statistics Simple random sampling and sampling distribution of sample mean, central limit theorem, normal approximation to the binomial Differentiation between a population and a sample, how to use a statistic to estimate a population parameter, confidence interval and its interpretation, inferences of population mean and proportion Confidence interval for population mean, Sample size needed for estimating the population mean with a specified confidence level and specified width of the interval Hypothesis testing: in terms of how to set up Null and Alternative hypotheses, understanding Type I and Type II errors, performing a statistical test for the population mean p-value, how to compute it and how to use it Inferences about μ with σ unknown: the t-distribution and the assumptions required to check in order to use it How to compare the mean of two populations for independent samples: using pooled variances t-test versus separate variances t-test How to compare the mean of two populations for paired data How to compare two population proportions Using contingency table and the Chi-square test of independence Understanding concepts related to linear regression models including, least squares method, correlation, inferences about the parameters in the linear regression model (reference books) The course the course is taught in Italian so textbooks are in Italian: - G. Cicchitelli, Statsitica: Principi e Metodi, Pearson Education, 3/Eds - Sebastiani M. R. (2015) “Esercitazioni di statistica”. Esculapio Editore, 3° edizione. For English speaking students a textbook is: Introductory Statistics for Business and Economics by Thomas H. Wonnacott and Ronald J. Wonnacott John Wiley & Sons Inc; International 2 Revised ed Notes and handout (in Italian) are available at the web page of the course.
Dates of beginning and end of teaching activities	From 25/02/2020 to 31/05/2020
Delivery mode	Traditional At a distance
Attendance	not mandatory
Evaluation methods	Written test Oral exam