Econometrics I [ECF 3311] Seminar 4 Flashcards

Vocabulary terms and definitions covering simple linear regression estimates, variances, and the Gauss-Markov Theorem based on the Econometrics I Seminar 4 materials.

ECF 3311

The course code for Econometrics I at The University of Zambia, Department of Economics.

Dependent Variable ($Y_i$)

In this specific seminar, it is defined as Talk time consumption.

Independent Variable ($X_i$)

In this specific seminar, it is identified as Income.

$\hat{\beta}_0$ and $\hat{\beta}_1$

The regression estimate values representing the intercept and the slope of the regression line.

Homoscedastic variance ($\sigma^2$)

The constant variance of the error term ($u_i$) in a regression model.

Standard Errors

Estimates that measure the precision or statistical accuracy of the regression coefficients $\hat{\beta}_0$ and $\hat{\beta}_1$.

Stata

The statistical software platform used in the seminar to calculate standard errors and perform regression analysis.

Gauss-Markov Theorem

A theorem stating that under the Classical Linear Regression Model Assumptions, the Ordinary Least Squares (OLS) estimators are the Best Linear Unbiased Estimators (BLUE).

Classical Linear Regression Model (CLRM) Assumptions

The set of conditions required to be met for the Gauss-Markov Theorem to hold regarding regression estimates.

Dr John Musantu

The Module Leader for the Econometrics I [ECF 3311] course.