84149 - Statistics for Social Sciences

Academic Year 2021/2022

  • Teaching Mode: Traditional lectures
  • Campus: Rimini
  • Corso: Second cycle degree programme (LM) in Tourism Economics and Management (cod. 8609)

Learning outcomes

This course aims to provide basic statistical techniques for investigating socio-economic phenomena, with specific attention to the tourism domain. Particular emphasis is addressed to the descriptive and inferential techniques for data analysis also in a multidimensional context. At the end of this course, the student will be able to i) collect and organize tourism data; ii) arrange a sample survey and build a questionnaire for his/her own research purposes; iii) perform statistical analysis in the tourism field.

Course contents

  • Part 1: Statistical inference

    Sample and population; sampling distribution of the mean; hypothesis testing and confidence intervals. LAB: R tutorial on data visualization, hypothesis testing and confidence intervals.

    • Part 2: Regression

      Simple linear regression; multiple linear regression; least squares estimation; inference for the model coefficient; model checking; anova; extension of linear regression. LAB: R tutorial on linear regression with real case studies.


    • Statistical Methods for the Social Sciences, Global Edition, 5/E. Agresti (2017).
    • An Introduction to Statistical Learning, with Applications in R. James, Witten, Hastie and Tibshirani (2013).

    Teaching methods

    Frontal lectures using slides, notes at the board/ipad. Laptop when using R for the applied tutorials.

    Assessment methods

    The exam aims at evaluating students' understanding of the all topics included in the syllabus; it will be evaluated the ability to:

    - produce statistical analysis in R (e.g. descriptive statistics, tests and model fitting);

    - interpreting the output of the statistical analysis;

    - draw conclusions.

    Exam is a computer-based quiz with questions on all the topics included in the syllabus; the quiz will be taken in a university LAB if the pandemic restrictions allow this, otherwise the exam will be administered in remote and supervised via Zoom.

    Exam questions can be true/false; multiple choice with three options; numerical. Some of the multiple choice questions require to 'select only one option', others require 'select one or more'. The numerical questions require the student to input a number (typically it is required to compute the answer using the software R). More details about the structure of the exam will be given during the course; a sample of possible questions will be uploaded in the webpage of the course on https://virtuale.unibo.it.

    For each correct answer you get 1 point, 0 points in case of mistake. A positive grade is expressed in a scale between 18 (sufficient) and 30L (excellent). A grade below 18 means you have failed the exam (denoted as 'Respinto' in the webpage 'almaesami').



    A couple of days after the exam the teacher will comunicate grades (via almaesami) and the date set for registration. Students can reject the grade obtained at the exam once. To this end, he/she must email a request to the instructor within the date set for registration. The instructor will confirm reception of the request within the same date.


    Teaching tools

    Software: R (http://www.r-project.org/) e RStudio (https://rstudio.com/).

    Office hours

    See the website of Massimo Ventrucci


    Sustainable cities Responsible consumption and production

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