Programme

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

Core Documentation

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

Type of delivery of the course

6 hours per week of classes by the lecturer and 2 hours per week of tutorials plus 2 hours per week of exercise tutoring.

Type of evaluation

Examination procedure - Students are not allowed to switch to parallel courses. Exams must be made with the lecturer you are assigned to. - The written test consists of: exercises, multiple choice questions, theoretical questions. - No notes and/or books are allowed to be brought to the exam room. Students must bring the tables of probability distributions available on the course website. - To pass the exam one must pass both the practical and the theoretical questions. - On passing the written exam the result will be recorded on GOMP, unless an oral exam is requested by the lecturer. - Students who get a grade below 11/30 are not allowed to take the exam in the next exam session.

Programme

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

Core Documentation

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.

Type of delivery of the course

6 hours per week of classes by the lecturer and 2 hours per week of tutorials

Attendance

frequency is recommended but not mandatory

Type of evaluation

Examination procedure (September 2020 exam session) - The written test lasts two hours. - The written test consists of: exercises, multiple choice questions, theoretical questions. - It is not allowed to introduce any notes and/or books in the exam room. Students are allowed to bring only the tables of probability distributions available on the course website. - The written test is passed if the student obtains sufficiency both in the practical and in the theoretical part. - A candidate who has passed the written test may request that the grade obtained in the written exam be recorded, unless an oral exam is requested by the lecturer. - A candidate who has passed the written test may request to perform the oral exam. _______________________________________________________________ NOTE Due to the COVID-19 health emergency, the summer exam session will take place remotely as follows: an oral exam will be preceded by a multiple choice test before the oral exam (art. 2 paragraph 3 of the DR n. 703/2020, "The oral exam, which is however crucial for the attribution of the final assessment, may take into account one or more written or practical tests, such as project papers, etc., done prior to the oral examination."). On the exam date, the multiple choice test will be made available on Moodle. The test must be completed in 30/45 minutes. This test will consist of multiple choice questions (calculators and probability distribution tables may also be needed) randomly extracted for each student from a large deposit. The questions include one, and only one, correct answer. Surveillance applications provided by the University might be used. At the end of the written test, the outcome will be communicated. We will proceed with the subsequent call for the oral test that will take place on Teams. It is absolutely necessary that you read the procedures prepared by the University and activate the necessary software. You will receive more precise instructions via Gomp closer to the exam. ___________________________________________

Programme

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

Core Documentation

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

Type of delivery of the course

6 hours per week of classes by the lecturer and 2 hours per week of tutorials plus 2 hours per week of exercise tutoring.

Type of evaluation

Examination procedure - Students are not allowed to switch to parallel courses. Exams must be made with the lecturer you are assigned to. - The written test consists of: exercises, multiple choice questions, theoretical questions. - No notes and/or books are allowed to be brought to the exam room. Students must bring the tables of probability distributions available on the course website. - To pass the exam one must pass both the practical and the theoretical questions. - On passing the written exam the result will be recorded on GOMP, unless an oral exam is requested by the lecturer. - Students who get a grade below 11/30 are not allowed to take the exam in the next exam session.

Programme

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

Core Documentation

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.

Type of delivery of the course

6 hours per week of classes by the lecturer and 2 hours per week of tutorials

Attendance

frequency is recommended but not mandatory

Type of evaluation

Examination procedure (September 2020 exam session) - The written test lasts two hours. - The written test consists of: exercises, multiple choice questions, theoretical questions. - It is not allowed to introduce any notes and/or books in the exam room. Students are allowed to bring only the tables of probability distributions available on the course website. - The written test is passed if the student obtains sufficiency both in the practical and in the theoretical part. - A candidate who has passed the written test may request that the grade obtained in the written exam be recorded, unless an oral exam is requested by the lecturer. - A candidate who has passed the written test may request to perform the oral exam. _______________________________________________________________ NOTE Due to the COVID-19 health emergency, the summer exam session will take place remotely as follows: an oral exam will be preceded by a multiple choice test before the oral exam (art. 2 paragraph 3 of the DR n. 703/2020, "The oral exam, which is however crucial for the attribution of the final assessment, may take into account one or more written or practical tests, such as project papers, etc., done prior to the oral examination."). On the exam date, the multiple choice test will be made available on Moodle. The test must be completed in 30/45 minutes. This test will consist of multiple choice questions (calculators and probability distribution tables may also be needed) randomly extracted for each student from a large deposit. The questions include one, and only one, correct answer. Surveillance applications provided by the University might be used. At the end of the written test, the outcome will be communicated. We will proceed with the subsequent call for the oral test that will take place on Teams. It is absolutely necessary that you read the procedures prepared by the University and activate the necessary software. You will receive more precise instructions via Gomp closer to the exam. ___________________________________________

Programme

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

Core Documentation

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

Type of delivery of the course

6 hours per week of classes by the lecturer and 2 hours per week of tutorials plus 2 hours per week of exercise tutoring.

Type of evaluation

Examination procedure - Students are not allowed to switch to parallel courses. Exams must be made with the lecturer you are assigned to. - The written test consists of: exercises, multiple choice questions, theoretical questions. - No notes and/or books are allowed to be brought to the exam room. Students must bring the tables of probability distributions available on the course website. - To pass the exam one must pass both the practical and the theoretical questions. - On passing the written exam the result will be recorded on GOMP, unless an oral exam is requested by the lecturer. - Students who get a grade below 11/30 are not allowed to take the exam in the next exam session.

Programme

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

Core Documentation

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.

Type of delivery of the course

6 hours per week of classes by the lecturer and 2 hours per week of tutorials

Attendance

frequency is recommended but not mandatory

Type of evaluation

Examination procedure (September 2020 exam session) - The written test lasts two hours. - The written test consists of: exercises, multiple choice questions, theoretical questions. - It is not allowed to introduce any notes and/or books in the exam room. Students are allowed to bring only the tables of probability distributions available on the course website. - The written test is passed if the student obtains sufficiency both in the practical and in the theoretical part. - A candidate who has passed the written test may request that the grade obtained in the written exam be recorded, unless an oral exam is requested by the lecturer. - A candidate who has passed the written test may request to perform the oral exam. _______________________________________________________________ NOTE Due to the COVID-19 health emergency, the summer exam session will take place remotely as follows: an oral exam will be preceded by a multiple choice test before the oral exam (art. 2 paragraph 3 of the DR n. 703/2020, "The oral exam, which is however crucial for the attribution of the final assessment, may take into account one or more written or practical tests, such as project papers, etc., done prior to the oral examination."). On the exam date, the multiple choice test will be made available on Moodle. The test must be completed in 30/45 minutes. This test will consist of multiple choice questions (calculators and probability distribution tables may also be needed) randomly extracted for each student from a large deposit. The questions include one, and only one, correct answer. Surveillance applications provided by the University might be used. At the end of the written test, the outcome will be communicated. We will proceed with the subsequent call for the oral test that will take place on Teams. It is absolutely necessary that you read the procedures prepared by the University and activate the necessary software. You will receive more precise instructions via Gomp closer to the exam. ___________________________________________

Programme

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

Core Documentation

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

Type of delivery of the course

6 hours per week of classes by the lecturer and 2 hours per week of tutorials plus 2 hours per week of exercise tutoring.

Type of evaluation

Examination procedure - Students are not allowed to switch to parallel courses. Exams must be made with the lecturer you are assigned to. - The written test consists of: exercises, multiple choice questions, theoretical questions. - No notes and/or books are allowed to be brought to the exam room. Students must bring the tables of probability distributions available on the course website. - To pass the exam one must pass both the practical and the theoretical questions. - On passing the written exam the result will be recorded on GOMP, unless an oral exam is requested by the lecturer. - Students who get a grade below 11/30 are not allowed to take the exam in the next exam session.

Programme

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

Core Documentation

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.

Type of delivery of the course

6 hours per week of classes by the lecturer and 2 hours per week of tutorials

Attendance

frequency is recommended but not mandatory

Type of evaluation

Examination procedure (September 2020 exam session) - The written test lasts two hours. - The written test consists of: exercises, multiple choice questions, theoretical questions. - It is not allowed to introduce any notes and/or books in the exam room. Students are allowed to bring only the tables of probability distributions available on the course website. - The written test is passed if the student obtains sufficiency both in the practical and in the theoretical part. - A candidate who has passed the written test may request that the grade obtained in the written exam be recorded, unless an oral exam is requested by the lecturer. - A candidate who has passed the written test may request to perform the oral exam. _______________________________________________________________ NOTE Due to the COVID-19 health emergency, the summer exam session will take place remotely as follows: an oral exam will be preceded by a multiple choice test before the oral exam (art. 2 paragraph 3 of the DR n. 703/2020, "The oral exam, which is however crucial for the attribution of the final assessment, may take into account one or more written or practical tests, such as project papers, etc., done prior to the oral examination."). On the exam date, the multiple choice test will be made available on Moodle. The test must be completed in 30/45 minutes. This test will consist of multiple choice questions (calculators and probability distribution tables may also be needed) randomly extracted for each student from a large deposit. The questions include one, and only one, correct answer. Surveillance applications provided by the University might be used. At the end of the written test, the outcome will be communicated. We will proceed with the subsequent call for the oral test that will take place on Teams. It is absolutely necessary that you read the procedures prepared by the University and activate the necessary software. You will receive more precise instructions via Gomp closer to the exam. ___________________________________________