# 96321 - STATISTICS AND PROGRAMMING

• Moduli: Laura Anderlucci (Modulo 1) Marco Novelli (Modulo 2) Marco Novelli (Modulo 3)
• Campus: Bologna
• Corso: First cycle degree programme (L) in Economics, Politics and Social Sciences (cod. 5819)

## Learning outcomes

By the end of the course students have acquired knowledge of the main statistical techniques for exploratory data analysis and the fundamental concepts of probability and inference from random samples. Moreover, they have developed skills to formalize and to solve the basic statistics problems using R.

## Course contents

Descriptive Statistics

Basic concepts. Frequency distributions. Describing data by graphs. Descriptive summary statistics: central tendency and variability measures. Association in contingency tables. Simple linear regression and correlation.

Probability

Basic concepts and Bayes theorem. Random variables. Central Limit theorem.

Statistical Inference

Random samples and sampling distribution of statistics. Point and interval estimation. Hypothesis testing.

Programming (with R)

Introduction to R: downloading and installing R (RStudio), R language essentials, data entry. Univariate and bivariate descriptive statistics. Probability distributions. Point estimation, confidence intervals and hypotheses testing.

During the course, datasets and examples of applications to economics and social sciences will be illustrated.

Statistics textbook:

G. Cicchitelli, P. D'Urso, M. Minozzo (2021) "Statistics - Principles and Methods", first edition. Pearson Italia, Milano-Torino.

Programming textbook:

P. Dalgaard (2008) "Introductory statistics with R", second edition. Springer, New York, NY.

## Teaching methods

Lectures and lab sessions.

As concerns the teaching methods of this course unit, all students must attend Module 1, 2 [http://www.unibo.it/en/services-and-opportunities/health-and-assistance/health-and-safety/online-course-on-health-and-safety-in-study-and-internship-areas] on Health and Safety online.

## Assessment methods

Assessment will take place through written exams (no oral exams). The written test is aimed at assessing the student's ability to use the learned definitions, concepts and properties and in solving exercises. During the written exam, students can use the formula sheet that is provided on virtuale.unibo.it and a pocket calculator only. Students cannot make use of the textbook, probability distribution tables, personal notes and mobile phones (smart watch or similar electronic data storage or communication device are not allowed either).

During the semester, students will have the opportunity to take the full exam in three different appelli through the academic year, or to split assessment by taking a midterm halfway through the course, and then a final during the regular appelli (the overall grade is the average of the two tests).

The midterm will cover topics of Descriptive Statistics. It will include exercises and short essays.

The final will cover topics of Probability, Statistical Inference and Programming (with R). It will be a mix of multiple choice questions, exercises, and short essays.

The full exam will cover the whole course program.

In order to sit midterm/final or full exam, students must sign up on Almaesami. Lists generally close 2-3 days before the exam; it won't be possible to be added to the list after the deadline.

Students that, despite having passed the exam, do not feel represented by the obtained result can ask to have an additional (optional) oral exam on the whole program that can change the grade by +/-3 points.

## Teaching tools

Slides available on virtuale.unibo.it

Tutorials.

## Office hours

See the website of Laura Anderlucci

See the website of Marco Novelli

See the website of Marco Novelli