88089 - Statistics

Course Unit Page

SDGs

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.

Quality education Decent work and economic growth

Academic Year 2021/2022

Learning outcomes

The aim is to lead the student in learning the basic statistical notion. The first theoretical part introducing the basic statistics is followed by an application part with practical exercises.

Course contents

The course program is organized in three parts as described below.

Exploratory Data Analysis

The data matrix. Types of variables. Frequency tables. Graphical representations. Summary measures of position and dispersion. Association of two quantitative variables, covariance and correlation coefficient. Outline of simple linear regression.

Probability Theory

Random experiment, sample space and events, probability measure. Conditional probability, independence. Random variables. Expected value and variance of a random variable. Discrete and continuous random variables. Bernoulli and binomial distribution. Gaussian distribution.

Inferential Statistics

Random sampling. Parametric statistical models. Sampling distributions. Point estimation. Bias and mean squared error. Confidence intervals for the mean of a Gaussian population. The Student t distribution. Approximate confidence interval for a probability. Hypothesis testing on the mean of a Gaussian population. The p-value. Inference on a proportion.

Readings/Bibliography

Nevo D. (2017). Making sense of data through statistics: an introduction. Legerity Digital Press. Second Edition.

Teaching methods

Teacher's lectures and tutorials.

Assessment methods

For attending students, there are 3 tests during the Statistics course, otherwise, is possible to do only one full test in the ordinary examination session.

To pass the exam the student score has to be greater than or equal to 18 in the full examination and in partial tests (for attending students) the average score has to be not less then 18.

If the student does not pass the examination in the following course session, he/she can give back it only in September session.

Teaching tools

Slides of the course, materials for self-assessment.

Office hours

See the website of Silvia Bianconcini