84149 - Statistics for Social Sciences

Academic Year 2019/2020

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.

    • Part 3: Classification

      Logistic regression, linear discriminant analysis, some notions on generalized linear models. LAB: R tutorial on classification techniques applied to real case studies.

    Readings/Bibliography

    • 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 (e.g. descriptive statistics, tests and model fitting);

    - interpret the output of the analysis (including the output produced by the software R).

    Exam is a quiz on EOL/Zoom. There will be questions on all the topics included in the syllabus; some questions are multiple choice while others require to enter a number (the use of software R is required to answer the questions requiring a number).

    Teaching tools

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

    Office hours

    See the website of Massimo Ventrucci

    SDGs

    Sustainable cities Responsible consumption and production

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