STATISTICA PER L'ECONOMIA

Degree course: 
Corso di First cycle degree in ECONOMICS AND MANAGEMENT
Academyc year when starting the degree: 
2018/2019
Year: 
2
Academyc year when helding the course: 
2019/2020
Language: 
Italian
Credits: 
11
Period: 
Second semester
Standard lectures hours: 
121
Requirements: 

The topics covered in the course of Mathematics (code ECO0011)

Final Examination: 
Orale

Students will be evaluated in their knowledge and understanding through the means of a written exam concerning theory and exercises.

Assessment: 
Voto Finale

Students will acquire a good understanding of the statistical tools and techniques related to descriptive statistics, probability and inferential statistics covered in the course, as well as the ability to employ them in economic and business applications.

DESCRIPTIVE STATISTICS
−Classification of the variables
−Absolute, relative and percentage frequencies.
−Graphical representation of the variables:
1. Pie charts, bar charts, histograms.
2. Cumulative distribution function.

−Numerical description of the variables:
−Measures of central tendency: analytic means (arithmetic and geometric mean); median and quartiles, mode.
−Measures of variability.
−Concentration measures.
- Time series and index numbers

−Bivariate analysis:
−Scatter plot and contingency table. Joint, marginal, conditional distributions. Conditional mean.
−Independence.
−Chi-square measure of association
−Linear dependence between two variables: covariance and correlation coefficient.

- Simple linear Regression:
- Ordinarily least square estimators
- Prediction
- R2 coefficient of determination.

- Examples and applications of some descriptive statistics tools with Excel.

INFERENTIAL STATISTICS
Random variables (r.v.):
−Review of Bernoulli, Binomial, Poisson distributions.
−Review of uniform, normal, exponential distributions.

Point estimation
−Random sample, estimator and estimate: definition.
−Sample mean and sample variance: definition and properties.
−Central Limit Theorem
−Properties of estimators: unbiasedness, asymptotic unbiasedness, efficiency, consistency.

Confidence Intervals
−Definition of Confidence Intervals (C.I.)
−C.I. for the mean of the normal population: variance known and unknown; Student T distribution.
−C.I. for the proportion of a Bernoulli population.

Test of Hypothesis
−Introduction
−Test for the mean of the normal population: variance known and unknown
−Test for the proportion of the Bernoulli population.
−Test for the variance of the normal population.

Two populations
−C.I. and test for the difference in the means of two normal populations: variance known and unknown.

- G. CICCHITELLI, P. D’URSO, M. MINOZZO (2017), Statistica: principi e metodi, Terza edizione, Pearson Italia, Milano (Chapters 1-6; 9-11; 13 - 14; 16 - 21)
- Notes and additional exercises will be available on e-learning page.

Convenzionale

The theoretical lessons will be accompanied by weekly exercises classes.

Updated information about the office hour are available at the Professor's web page.

Professors