B1751 - Statistics for Social Sciences

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.

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.

Considering the nature of the activities and the teaching methods adopted, the attendance of this training activity requires all students to participate in the safety modules 1 and 2 on studying places [https://elearning-sicurezza.unibo.it/ ] in e-learning mode.

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.

Exam questions can be: true/false; multiple choice (either 'select only one option' or 'select one or more'); numerical (e.g., compute the answer using the software R and input the number); open questions (e.g., comments to statistical software outputs, definitions etc). 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 (this denoted as 'Respinto' in the webpage 'almaesami').

REGISTRATION

A few 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 only 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/) and RStudio (https://rstudio.com/).

Office hours

See the website of Massimo Ventrucci