B1751 - STATISTICS FOR SOCIAL SCIENCES

Conoscenze e abilità da conseguire

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.

Contenuti

Estimating causal effects with experimental data. Outcome and treatment variables. Potential outcomes. Factual and Counterfactual outcomes. Individual treatment effects. The fundamental problem of causal inference. Randomization. The difference in means estimator.

Predicting outcomes with linear regression using observational data. Interpretation of intercept and slope coefficient.

Probability. Bernoulli, Normal, Standard Normal. Properties of the Standard Normal. Cumulative distribution function of the Standard normal distribution.

Statistical inference. Sample statistics and population parameters. Law or large numbers and central limits theorem. Estimates and estimators. Sampling distribution of an estimator. Confidence intervals. 95% CI for the sample mean. 95% CI for predicted outcomes in a linear regression model. 95% CI for the difference-in-mean estimator. The difference in means estimator as the slope coefficient of a linear model with X a binary treatment variable. Testing hypothesis on the slope coefficient in linear regression.

Advanced topics in linear regression. Multiple linear regression. R2. Case study Advertising.

Designing a survey in Social Sciences.

 

Testi/Bibliografia

Textbook2: An Introduction to Statistical Learning, with Applications in R. James, Witten, Hastie and Tibshirani (2013).

Further readings: Statistical Methods for the Social Sciences, Global Edition, 5/E. Agresti (2017).

Metodi didattici

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

In considerazione della tipologia di attività e dei metodi didattici adottati, la frequenza di questa attività formativa richiede la preventiva partecipazione di tutti gli studenti ai moduli 1 e 2 di formazione sulla sicurezza nei luoghi di studio, [https://elearning-sicurezza.unibo.it/] in modalità e-learning.

Modalità di verifica e valutazione dell'apprendimento

The exam aims to evaluate students’ understanding of all the topics covered in the syllabus. It will assess their ability to:

• produce statistical analyses in RStudio (e.g., descriptive statistics, hypothesis testing, and model fitting);

• interpret the output of statistical analyses;

• draw appropriate conclusions.

The exam consists of two parts: a take-home assignment (using RStudio) and a computer-based quiz covering all topics included in the syllabus. The quiz accounts for 70% of the final score, and the take-home assignment accounts for 30%.

The computer-based quiz includes true/false, multiple-choice (both “select one” and “select one or more”), numerical(e.g., compute the answer using R and enter the result), and open-ended questions (e.g., interpreting statistical software outputs, providing definitions, or short written comments).

A sample of possible questions will be discussed during the final lecture.

For each correct answer, you receive 1 point; incorrect answers receive 0 points.

Final grades are expressed on a scale from 18 (sufficient) to 30L (excellent). A grade below 18 indicates that the exam has not been passed — this is shown as “Respinto” on the AlmaEsami webpage.

 

REGISTRATION

A few days after the exam, the instructor will communicate the grades via AlmaEsami and announce the date scheduled for grade registration.

Students may reject the grade obtained in the exam only once. To do so, they must email a request to the instructor beforethe registration date. The instructor will confirm receipt of the request by that same date.

Strumenti a supporto della didattica

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

Orario di ricevimento

Consulta il sito web di Massimo Ventrucci