Sociology

1 Introduction to statistics 2 Statistical distributions 3 Graphical displays 4 Means 5 Variability 6 Shape 7 An overview of statistical summaries 8 Bivariate distributions: dependency 9 Bivariate distributions: regression 10 Bivariate distributions: correlation 11 Probability 12 Random variables 13 Some probability distributions 14 Law of large numbers and central limit theorem 15 Population, sample, sampling distributions 16 Point estimation 17 Interval estimation.

There are no specific requirements. No preparatory courses are required.

Cicchitelli, G., D'Urso, P., Minozzo, M. - Statistica. Principi e metodi. Quarta edizione (2022), Pearson.

Lecture attendance is not mandatory but is strongly recommended given the know-how-oriented course setting.

The evaluation is performed by a final written examination, carried out during the scheduled exam sessions (3 calls in June / July session, 1 call in the September session, 2 calls in January / February session). The written exam consists of 21 exercises with both theoretical and practical questions. The test is intended to assess knowledge and understanding and the student's ability to apply knowledge and understanding. The student must indicate the correct answer and return the calculations necessary to obtain the indicated result. For completing the test, the students will have 75 minutes and can use a calculator and statistical tables. In itinere evaluation will be performed. The course includes two partial exams. The first partial exam, covering univariate and bivariate descriptive statistics, consists of 14 questions including both theoretical and practical (exercises) items. The second partial exam, covering inferential statistics, consists of 7 questions including both theoretical and practical (exercises) items. Each correctly, thoroughly, and comprehensively answered question will be assigned a score (1 or 2 points depending on the difficulty of the question). The grade for each partial exam will be the sum of the scores obtained for each question. The rules for the two partial exams are as follows: 1. To pass the exam, it is necessary to achieve a passing grade in both partial exams. 2. Access to the second partial exam is permitted only if the first partial exam has been passed. 3. If the first partial exam is passed but the grade is rejected, the student must take the full exam in one of the official exam sessions. 4. If both partial exams are passed, the exam will be officially recorded with a grade equal to the sum of the grades from the two partial exams. If the grade is rejected, the student must take the full exam in one of the official exam sessions. For the partial exams, students will have 45 minutes and may use a calculator and statistical tables. In determining the final grade, the assessment takes into account the following elements: 1. the thought process followed by the student in solving the proposed questions; 2. the correctness of the procedure chosen by the student to get the solution; 3. the adequacy of each solution proposed by the student, considering both the type of question and his expected competences; 4. the use of a correct and proper language. A grade of at least 18/30 is required to pass the exam. Students must demonstrate a) to have acquired a sufficient knowledge of the topics covered in the course and b) to be able to identify statistical techniques and tools - simple but adequate - for the solution of the proposed real problems. The grade 30/30 cum laude is assigned to those students who demonstrate an excellent knowledge of all the topics covered during the course and strong critical thinking skills. Students must also demonstrate to be able to identify the most suitable statistical techniques and tools, both simple and complex, for solving real problems.

In-class sessions comprise didactic lectures, practical sessions, hands-on exercises, demonstrations, discussion. Lectures will be aimed at stimulating both interaction with students and their problem solving skills. Therefore, each topic will be supplemented by examples and hands-on exercises in order to facilitate the understanding of statistical tools and their use in social issues. The textbook comes with an online platform providing tutoring for the exercises and self-assessment tools. This will facilitate students in preparation for the exam.

Arguments considered are: frequency distributions, graphics, measure of central tendency (mean, mode, median), measure of dispersion (standard deviation, variance, variation coefficient), bivariate contingency tables, correlation analysis (covariance, correlation coefficient), regression analysis, probability, random variables, probability distributionss, estimators, confidence interval.

No prerequisites are required.

Zealure C. Holcomb ,Fundamentals of Descriptive Statistics, Taylor and Francis, 1998. Casella , G., Berger, R.L, Statistical Inference, (2001).

Lectures.

THE EXAMINATION TEST IS UNIQUE and consists of multiple-choice questions to be taken in presence on the SAPIENZA ELEARNING platform via PC. The exam will be conducted in a classroom equipped with a PC. The test consists of 21 questions, with both theoretical and practical questions (exercises) designed to test knowledge and understanding and the ability to apply knowledge and understanding.

Class.