2/56/024 - SOCIAL STATISTICS
Academic Year 2021/2022
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ISABELLA SULIS (Tit.)
- Teaching style
- Lingua Insegnamento
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The course aims to provide students the knowledge and interpretation of basic statistical tools for the analysis of economic, political and social phenomena in accordance with the Dublin Descriptors (I-V).
To this end, the course introduces the main statistical univariate and bivariate methodologies and the basic concepts of inferential statistics; knowledge necessary in the social sciences to obtain and processing information and making decisions.
At the end of the course it is expected that students are able to (i) critically interpret the information coming from social surveys and officially statistics daily posed to their attention, (ii) select and use the appropriate statistical tools in relation to the informative purposes of the issues under their attention; (Iii) process and synthesize statistical information with awareness , (iv) communicate and argue results to specialists and non-specialists with the necessary awareness regarding the validity of the methods used, their application, the potentialities and, at the same time, the limits. The course also aims to provide students with the knowledge necessary for them to develop further insights, individually, and making judgments.
At the end of the course the student will have acquired the skills necessary to undertake further studies (a second cycle academic degree -master degree-- in the field of social sciences).
The following mathematical notions are useful to the understanding of the course content. Elements of set theory (operations, relations, functions, sets numbers, natural, rational and real numbers), concept of a variable’s function (generality, graphical representation, properties, elementary functions such as straight line, parabola, polynomial exponential and logarithmic). Concept of limit, derivative, integral.
- Introduction to statistical methodology: description and inference
- Sampling and measurement: variables and their measurement; randomization; sampling and non sampling variability; other probabilities sampling methods.
- Descriptive statistics: data description, statistical distributions and their representation; measuring central tendency, measures of variation; sample statistics and population parameters.
- Probability distributions: probability distributions for discrete and continuous variables; the normal probability distribution; sampling distributions; sampling distributions of sample means;
- Estimation: point estimation; confidence intervals of a mean; confidence intervals of a proportion; choice of sample size.
-Significance Tests: elements of a significant test; significant test for means; significant test for proportions; decision and types of errors in tests of hypotheses; small-sample inference for a mean
-Comparison of two groups: comparing two means; comparing two proportions.
-Analysing association between categorical variables: contingency tables and measures of associations; chi-squared test of independence; measuring association between ordinal variables.
-Linear relations, correlation and regression: linear relationships; the correlation; the least squared prediction equation; the linear regression model.
The course consists of 27 lectures plus tutorial activities.
The tutorial activities will be held weekly and will be organized in classes of 2 hours.
Teaching activities will be carried out mainly face to face, integrated and "augmented" with online strategies,
in order to guarantee its use in an innovative and inclusive way.
Verification of learning
The assessment consists of a written exam which contains questions and statistical exercises/practical problems and a meeting aiming at the discussion of the outcome of the written exam.
Students have to provide to own the necessary knowledge for describing, processing and synthesizing statistical information with awareness of the comparative advantages, effectiveness and limits of methods adopted.
The exam score is expressed in 30 points scale.
The date scheduled for the discussion of the outcome of the written exam will be announced the day of the written exam. The discussion has the main aims to allow students to discuss the contents of their written exam with the lecturer and to have clarifications on their final assessment.
The written examination can be divided in two parts: an intermediate exam concerning the contents of part 1 of course (the exam will be scheduled during the course, between the first and second part of the program) and a final exam containing questions and practical problems on topics explained during the second part of the course.
The assessment in the intermediate exam is provided on a scale from A to D (A=27-30, B=23-26, C=18-22, D=insufficient).
The discussion of the both written exams (intermediate and final) is scheduled after the final written exam.
The final assessment of the two written exams is provided on a 30 points scale.
The intermediate exam can be taken only in the exam section of April/May. The second part of the exam has to be taken in the sections of June/July or September.
Based on the contextual conditions related to the Covid-19 pandemic, the intermediate exams could be cancelled.
Important aspects in determining the final assessment:
The final mark in the written exam takes into account the following aspects:
1. the logic followed by the student in the resolution of the questions;
2. the degree of adequacy to the identified procedure for the solution of question;
3. the adequacy, from a statistical point of view, of the proposed method according to the statistical skills that the student is expected to have acquired at the end of the course;
4. the ability to comunicate and discuss the results;
5. the use of an appropriate statistical language;
6. the use of an appropriate statistical-mathematical notation.
The fulfilment of the first two aspects is a necessary condition to get a positive evaluation.
The fulfilment also of aspects 3 and 4 allows to get an overall achievement more than positive, which depends on clearness and completeness of the answers provided. Final marks higher than 27 will be awarded to written exams which meets all six aspects.
Agresti A. – Finlay B (2009), Statistical Methods for the Social Sciences, Pearson, 4th edition, Upper Saddle River, N.J: Pearson Prentice Hall.
Agresti A. Finlay B., Statistica per le Scienze Sociali, Pearson Prentice Hall, Milano, 2009
Borra S., Di Ciaccio A. Statistica. Metodologie per le scienze economiche e sociali. McGraw-Hill, Milano, 2008
Porcu M., Tedesco N., Problemi di Statistica in ambito sociale ed economico, Pearson Education, Milano, 2007 (Eserciziario)
The link to the teaching material will be available on the lecturer's website
For information, send an email to: email@example.com