Econometrics - Simple Linear Regression | Expectation and variance of OLS | Gauss Markov Theorem

Learn Econometrics Easily | Simple Linear Regression Analysis | Expectation and Variance | OLS Estimator | Basics of Econometric | What is Econometrics? | Ordinary Least square method | Gauss Markov theorem.


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What is econometrics| What is Simple linear regression analysis.
Econometrics is the branch of economics concerned with the use of mathematical methods (especially statistics) in describing economic systems.
Simple linear regression is a statistical method that allows us to summarize and study relationships between two continuous (quantitative) variables: One variable, denoted x, is regarded as the predictor, explanatory, or independent variable.

What is an OLS?
ordinary least squares (OLS) is a type of linear least squares method for estimating the unknown parameters in a linear regression model.

What is Gauss markov theorem?
the Gauss–Markov theorem, named after Carl Friedrich Gauss and Andrey Markov, states that in a linear regression model in which the errors have expectation zero, are uncorrelated and have equal variances, the best linear unbiased estimator (BLUE) of the coefficients is given by the ordinary least squares .

Expectation and Variance
The expected value (or mean) of X, where X is a discrete random variable, is a weighted average of the possible values that X can take, each value being weighted according to the probability of that event occurring. The expected value of X is usually written as E(X) or m.

The variance of a random variable tells us something about the spread of the possible values of the variable. For a discrete random variable X, the variance of X is written as Var(X).


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