- Docente: Alessandro Lubisco
- Credits: 10
- Language: Italian
- Moduli: Alessandro Lubisco (Modulo 1) Fabio Gobbi (Modulo 2)
- Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
- Campus: Bologna
- Corso: First cycle degree programme (L) in Political, Social and International Sciences (cod. 8853)
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from Feb 19, 2024 to May 23, 2024
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from Feb 21, 2024 to May 23, 2024
Learning outcomes
The course gives to the participants a wide introduction to the basic tools which are necessary to implement a quantitative analysis of real phenomena, with a double aim: to develop the student skills of interpretation and critical evaluation of statistical information and to ensure the knowledge of the essential methods allowing the production and elaboration of well-organized statistical data.
After attending the course, students are expected:
- to be familiar with the basic elements of exploratory and inferential statistics;
- to be able to read and understand specialized papers containing the results of quantitative analyses,
- to have the capability of evaluating the synthetic elaboration of a set of census or sample data;
- to have acquired the expertise necessary to apply some of the specific tools of statistical methodology useful for a thorough description and/or study of economic and social phenomena.
Course contents
Modulus One (February - March)
Elements of univariate exploratory statistics:
Classification of statistical units. Frequency distributions.
Graphical representation.
Main mean values: mode, median, average.
Measures of variability: deviance, variance, standard deviation, coefficient of variation. Statistical ratios and index numbers.
Measures of inequality: concentration.
Elements of bivariate exploratory statistics:
Two-way frequency distribution (absolute and relative) and conditional distributions.
Linear dependence: covariance e correlation. Linear Regression.
Modulus Two (April-May)
Critical review of the main tools of exploratory statistics.
Some essential elements of probability.
The most used discrete random variables: Binomial, Geometric, Hypergeometric, Poisson.
The most used continuous random variables: Uniform, Exponential, Gaussian, Chi-Squared, Student t-distribution.
Statistical inference : population, sample, statistics and estimators, sample distributions.
Confidence interval for estimating frequencies and mean values.
Test for checking the specific value of a frequency and of a mean value.
Test for comparing two frequencies.
Test for comparing two mean values.
Test for checking independence between two variables.
Readings/Bibliography
Modulus 1
Slide ed esercizi risolti messi a disposizione dal docente
Simone Borra, Agostino Di Ciaccio
Statistica - Metodologia per le scienze economiche e sociali, IV edizione
Editrice: McGraw-Hill, Milano, 2021 ; ISBN 978-88-386-9632-9
Fulvia Mecatti
Statistica di base - Come, quando, perché - III edizione
Editrice: McGraw-Hill, Milano, 2022 ; ISBN 978-88-386-5660-6
Modulus 2
In definition
Teaching methods
Front lessons with some exercise sessions
Assessment methods
Written test concerning the topics developed in the course.
Partial test at the end of each modulus.
Oral examination (optional).
- Evaluation scale:
30 e lode (A+) =excellent
29 - 30 (A) = very good
27 - 28 (B+) = good
25 - 26 (B) = fairly good
23 - 24 (C) = more than sufficient
21 - 22 (D) = sufficient
18 - 20 (E) = barely sufficient
Teaching tools
Teaching sheets and excercises will be available in the Web platform "virtuale.unibo.it"
Office hours
See the website of Alessandro Lubisco
See the website of Fabio Gobbi