Università Roma Tre

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

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.

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

L. Pieraccini, A. Naccarato. Lezioni di Statistica Descrittiva, Giappichelli, 2003.

D. Piccolo Statistica per le decisioni - ed. Il mulino 2004

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

Introductory Statistics for Business and Economics by Thomas H. Wonnacott and Ronald J. Wonnacott
John Wiley & Sons Inc; International 2 Revised ed
See also: http://host.uniroma3.it/docenti/mortera/statisticaNNO/statisticaNNO.htm

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

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.