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5 Steps in Econometric Analysis: Hypothesis, Model Specification, Estimation, Verification / Statistical Inference / Statistical Tests of Hypothesis, Forecasting and Policy

Population regression function and sample regression function; Estimator vs Estimate; Desirable properties of Estimators (Small sample properties - Unbiasedness, Efficiency, MVUE, Linearity, Mean Squared Error vs Large sample properties - Asymptotic Unbiasedness, Consistency)

Data collection - Observational data vs experimental data; Role of random sampling assumption;

4 Assumptions for Estimation (also known as Gauss-Markov Assumptions)

Estimation using Ordinary Least Squares (OLS) Approach

Properties of OLS regression line
Properties of OLS estimators (OLS estimators are BLUE); also known as the Gauss-Markov Theorem (when Gauss-Markov Assumptions are valid)
- https://www.youtube.com/watch?v=n5vh2CozAlU&list=PLwJRxp3blEvZyQBTTOMFRP_TDaSdly3gU&index=76&pp=iAQB
- 76 ⇒ 84
https://www.youtube.com/watch?v=vOBtEiij-fA&list=PLwJRxp3blEvZyQBTTOMFRP_TDaSdjjly3gU&index=14&pp=iAQB
14 ⇒ 20

Statistical Inference in SLR

Hypothesis testing basics - Basic intuition (Null Vs Alternative); Type of errors in statistical decision making (Type I vs Type II); sampling distribution of an estimator; statistic; critical values; Chi-squared, t and F tests; Confidence Interval approach to hypothesis testing

Measuring Goodness of fit (Coefficient of determination; R-squared or R^2 in SLR and their relationship; One-way ANOVA); Relationship between R^2 and F-statistic and t-statistic

OLS without intercept term; interpretation; OLS with change of origin and scale (Tutorial)

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Simple linear regression (SLR)

Relaxation of the Gauss-Markov Assumptions