Akademik Dersler - İçerik

To be able to define econometrics, explain the purpose of econometrics; To be able to define the concept of regression, and to list the data types; To be able to explain the methodology of econometrics.
To be able to explain the linear regression model; To be able to define the simple linear regression model and to explain its assumptions.
To be able to define the multiple linear regression model, and list its assumptions; To be able to test the partial regression coefficients and the overall significance of the model.
To be able to define regression models without intercept or constant term and explain their properties; To be able to express linear regression models with standardized variables; To be able to test linear and nonlinear constraints.
To be able to define artificial variables, to give examples, and to specify the types of models with artificial variables; Be able to explain in which case, how to include and interpret a slope dummy variable in a regression.
To be able to express in which case the mean of the error term 'u' is always zero and cosequences on estimations when the mean of the error term is not zero; To be able to express the concepts of perfect and strong multicollinearity and effects on parameter estimation; Identify the degree of multicollinearity and remedies to solve it.
To be able to express the causes and consequences of varying variance and to determine whether the errors in a regression model have varying variance; To be able to express the causes and consequences of autocorrelation; Be able to express how to test whether the residual distribution from a regression is significantly different from the normal.
To be able to express the concepts of structural form, reduced form, structural and reduced form parameters, internal and external variables; To be able to discuss the cause, consequences and solution of simultaneous equation deviation and to express the methods used in estimating simultaneous equation models.