D. Piccolo (2010) Statistica per le decisioni con R. Il Mulino, Bologna
Knowledge: Introductory-level concepts of probability and statistics. Acquired expertise: Students will acquire the ability to organize and analyze a real data set, by an adequate probabilistic model. Moreover, they will be able to critically understand features and limits of models and methods, illustrated during the course.
Courses required: Analysis I: Integral and Differential Calculus
Office hours by appointment
Type of Assessment
Oral and written examination. The exercises in the written test are selected from the teaching notes provided on the Moodle platform. The access to the oral exam is conditional to a score of at least 18/30 to the test. The oral exam consists of a discussion of the test and questions about the whole program. The final score is the average of the scores in the written and oral exams.
Descriptive statistics: frequency distributions, measures of location and variability. Statistical graphs. Introduction to probability. Conditional probability and independence. Bayes' formula. Discrete and continuous random variables. Introduction to statistical inference: point estimation, hypothesis tests and confidence intervals. Association and independence. Simple and multiple linear regression model. Introduction to software R.