48
Statistics
UNIVERSITÀ DEGLI STUDI DI NAPOLI "L'ORIENTALE"
Overview
Date/time interval
Syllabus
Course Objectives
The course aims to provide students with the knowledge and methodological tools necessary to develop and solve simple descriptive and inferential statistical problems, using a scientific calculator and/or the aid of statistical functions found in specific software (R and/or Excel).
EXPECTED LEARNING OUTCOMES
Autonomy of judgement: at the end of the course, with the acquisition of the foreseen CFUs, the students will be able to autonomously assess which methodological tools are most suitable for analysing statistical data according to a specific cognitive objective.
Communication skills: at the end of the course, with the acquisition of the foreseen CFUs, students will be able to interpret, comment and communicate the results obtained following the application of the methodological tools learned.
Learning ability: at the end of the course, with the acquisition of the foreseen CFUs, the students will be able to solve statistical problems that may arise in various disciplinary fields such as, for example, economics, sociology, political science, etc.
Course Prerequisites
Language skills and competences in Italian and mathematics acquired in any secondary school course.
Teaching Methods
The course is divided into theoretical lectures (30 hours) and related exercises (18 hours, spread over each individual lesson) that cover the teaching programme. The articulation of the lectures, in which everything that is explained is highly dependent on each topic covered previously, requires classroom participation and constant study, which are therefore strongly recommended. Self-assessment tests are foreseen for the attending students, which, through group work to be carried out at home on real data, aim to verify in itinere their ability to understand and use the statistical tools discussed in the lectures and their critical capacity in interpreting the results.
Assessment Methods
The examination consists of a written test (numerical exercises to be performed and commented on), the passing of which leads to an oral test (theoretical questions and interpretation of the results obtained in the exercises). The elements on which the assessment is based are the consistency of the tools used in relation to the delivery received, the ability to analyse the data and critically comment on the results obtained, and the correctness of the calculations. The assessment is expressed in thirtieths. The course is held in Italian and so is the final exam; however, if requested, any foreign students may take the exam in English.
Texts
A choice of one of the following texts:
in Italian:
- Borra & Di Ciaccio (2021) Statistics - Methodologies for the Economic and Social Sciences, 4/ed, McGraw Hill
- Piccolo (2020) Statistics for Decision Making, Il Mulino
or in English:
- Agresti, A. & Finlay, B. (2009) Statistical Methods for the Social Sciences, Fourth Edition, Pearson
Contents
STATISTICS (M-Z)
The course provides a basic knowledge of descriptive and inferential statistics. It has the dual objective of developing the ability to interpret and critically evaluate statistical data and the ability to produce and process basic univariate and bivariate analyses autonomously.
Topics
1. Summary statistics.
2. Frequency distributions and graphical representations of qualitative and quantitative variables.
3. Index numbers: indices of Laspeyres, Paasche, Fisher.
4. Statistical indices of location: arithmetic mean, median and mode. Weighted arithmetic mean. Percentiles and quartiles.
5. Classification of observations and outliers. Box-Plot.
6. Statistical indices of dispersion: variance, standard deviation, coefficient of variation, range, interquartile range, MAD.
7. Mutual variability and simple arithmetic difference.
8. Concentration and concentration ratio of the Gini index. The Lorenz curve.
9. Standardization of a variable. Measures of skewness and kurtosis.
10. Normal distribution and tables of the standardized Normal distribution.
11. Measures of association and measures of dependence between two variables: Chi-squared index, Eta-squared index and deviance decomposition, the covariance and the linear correlation coefficient.
12. Elements of Statistical Inference: Sampling. Central Limit Theorem.
13. Main point estimators: the sample mean, the sample variance and the sample proportion.
14. Statistical hypothesis testing. Chi-squared independence test.
15. Simple linear regression. Least squared estimation and properties of the regression line. The R-squared index.
Course Language
Italian
More information
Before the start of the semester, contact me by email (esarno@unior.it) to enroll in the course and enable the creation of a virtual classroom to download didactic material.