77290 - CRASH COURSE IN ECONOMETRICS

Scheda insegnamento

SDGs

L'insegnamento contribuisce al perseguimento degli Obiettivi di Sviluppo Sostenibile dell'Agenda 2030 dell'ONU.

Lavoro dignitoso e crescita economica

Anno Accademico 2018/2019

Programma/Contenuti

1. Descriptive statistics. Basic concepts. Mode, Median, Mean, Quantiles. Range, Interquartile difference, Variance, Standard Deviation. Covariance, Correlation. OLS line.
2. Probability and Random Variables. Discrete and continuous random variables: definition, distribution/density function, cumulative distribution function, moments and central moments. Expectation and Variance: definition and properties. Examples: Bernoulli, Uniform, Rectangular, Normal random variables. Properties of Normal random variables. Multiple random variables: marginal, conditional and joint distributions. Covariance and its properties. Linear correlation. Variance and covariance matrix.
3. Random sampling and sample distributions: Chi-square, Student's t, F. Sample Mean and ratio of two variances distributions. Use of the tables (Z, Chi-square, Student's t, F). Central limit theorems.
4. Estimation theory. Point estimation. Estimators properties. Statistical inference: confidence intervals (CI) and hypothesis testing (HT). CI and HT for an expectation, a proportion, a variance, a ratio of two variances, a difference between two expectations and two proportions.
5. The simple linear regression model: hypotesis, OLS estimation, confidence intervals and hypothesis testing, goodness of the fit.

Metodi didattici

Blackboard

Orario di ricevimento

Consulta il sito web di Gian Luca Tassinari