Statistics is a compulsory course aimed at introducing the basic statistical techniques for analysing data. Topics include exploratory data analysis, basic probability theory and statistical inference. Students will :
- learn to analyze and visualize data in R and create reproducible data analysis reports;
- acquire a theoretical understanding of statistical techniques and an appropriate critical sense in choosing the most suitable analysis for each data set;
- develop the ability to analyse real data sets and interpret the results.
There are no prerequisites, but students should have attended or are currently attending lectures on both Introduction to Computer Science and Programming and Mathematics.
- learn to analyze and visualize data in R and create reproducible data analysis reports;
- acquire a theoretical understanding of statistical techniques and an appropriate critical sense in choosing the most suitable analysis for each data set;
- develop the ability to analyse real data sets and interpret the results.
There are no prerequisites, but students should have attended or are currently attending lectures on both Introduction to Computer Science and Programming and Mathematics.
teacher profile teaching materials
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
- P. Newbold, W. Carlson, B. Thorne, Statistica, Pearson Education, 9° edizione
- 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
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:- P. Newbold, W. Carlson, B. Thorne, Statistica, Pearson Education, 9° edizione
- 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
Type of delivery of the course
6 hours per week of classes by the lecturer and 2 hours per week of tutorials.Type of evaluation
Examination procedure - 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. - Students who are awarded a "insufficient" grade in the written test are not allowed to take the exam in the next exam session.