Course Details

Review of Statistical Concepts

Random Variables Controlled vs. uncontrolled experimental data Discrete vs. continuous random variables Review of probability concepts Expected value Sample moments of a random variable The joint density functions Marginal density, conditional density and independence Covariance and correlation The Normal density T

The Simple Linear Regression Model

The econometric model The least squares principle Estimating the econometric model and interpreting the results The properties of the least squares estimate of an econometric model Inference and prediction in the Simple Linear Regression Model Interval estimation and hypothesis testing Evaluating the Simple Linear Regression Model

The Multiple Linear Regression Model

The econometric model with more than one independent variable The least squares principle Estimating the multiple regression and interpreting the results Inference and prediction in the multiple regression Single and joint hypothesis tests of the parameters of the econometric model Model specification issues Collinear variables

Non-linear effects in Regression models Binary variables Interactions between binary variables Functional form

Assessing Regression Models

 Heteroskedasticity Serial correlation Random regressors - instrument variable

Additional Topics in Regression Analysis Estimating regression models with panel data Regression models with binary dependent variable

Topics in Time Series Econometrics Stationary time series Spurious regression Tests for stationarity Cointegration For school level math training please visit www.12math.com