Sumários
TP06 - Regression Analysis (part 3)
2 Novembro 2023, 15:00 • Luís Silveira Santos
Multiple Linear Regression: functional form, interpretation of the regression coefficients (lin-lin, log-lin, lin-log, log-log), models with dummy variables, Gauss-Markov assumptions, OLS estimation, properties of the OLS estimator, confidence intervals and hypothesis testing, R-squared and the adjusted R-squared, heteroskedasticity (detection, testing and correction), autocorrelation (detection, testing and correction), multicollinearity (detection and correction), functional form misspecification (detection, testing and correction). Exercises.
Regression Analysis (part 3)
31 Outubro 2023, 14:00 • Jorge Caiado
Multiple Linear Regression: functional form, interpretation
of the regression coefficients (lin-lin, log-lin, lin-log, log-log), models
with dummy variables, Gauss-Markov assumptions, OLS estimation, properties of
the OLS estimator, confidence intervals and hypothesis testing, R-squared and
the adjusted R-squared, heteroskedasticity (detection, testing and correction),
autocorrelation (detection, testing and correction), multicollinearity
(detection and correction), functional form misspecification (detection,
testing and correction). Exercises.
TP05 - Regression Analysis (part 2)
26 Outubro 2023, 15:00 • Luís Silveira Santos
Simple Linear Regression: the coefficient of determination, confidence intervals and hypothesis testing, ANOVA and the F statistic, prediction (of the mean and of an individual). Exercises.
Regression Analysis (part 2)
24 Outubro 2023, 14:00 • Jorge Caiado
Simple Linear Regression: the coefficient of determination,
confidence intervals and hypothesis testing, ANOVA and the F statistic,
prediction (of the mean and of an individual). Exercises.
TP04 - Basic Statistics (part 3). Regression Analysis (part 1)
19 Outubro 2023, 15:00 • Luís Silveira Santos
Type I and Type II errors. Power of a test. Significance level. Correlation Analysis: correlation coefficient and its test statistic. Simple Linear Regression: the problem of estimation, OLS, Gauss-Markov assumptions, statistical properties of the OLS estimator, standard errors of the estimates. Exercises