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This video explains the detection methods for multicollinearity - simple correlation coefficient (r) and variance inflation factors (VIFs). It also include how to perform correlation matrix and VIFs using EViews, and how to interpret the results.

This video explains the definitions of perfect and imperfect multicollinearity, and its consequences.

This video explains three (3) remedies for heteroskedasticity - (i) Heteroskedasticity-Corrected Standard Error, (ii) Redefining the variables, and (iii) Weighted Least Squares (WLS).

This video explains the detection methods to detect heteroskedasticity, namely the Breusch-Bagan (BP) test and the White test. It also includes how to run/perform these tests in EViews.

This video explains the definitions of pure and impure heteroskedasticity and its consequences.

This video explains the remedies for serial correlation (also known as autocorrelation), which included Generalized Least Square (GLS) and Newey West Standard Error (SE). It also shows the derivation of GLS model using a hypothetical model.

This video explains the detection methods for serial correlation, also known as autocorrelation. Two tests were introduced: (1) Durbin Watson (DW) Test, and (2) Lagrange Multiplier (LM) Test. It also includes how and where to find these tests in EViews.

This video explains pure vs. impure serial correlation, also known as autocorrelation, and its consequences.

This video explains about dummy variables as independent variables, how does it work, how to interpret the estimated coefficient for dummy variable, how to generate a dummy variable yourself, and how to avoid dummy variable trap.

This video explains the problems we might encounter when an incorrect functional form is applied, and how to perform Ramsey RESET test in EViews to check if there is misspecification in the estimated regression model.

This video explains the importance of constant term in a model, what is a linear regression model, types of functional forms and how to interpret the estimated coefficient(s) in different types of functional forms.

This video explains how to develop a confidence interval for an individual estimated coefficient and how to perform F-test by comparing F-statistic and critical value from F-distribution.

This video explains all about t-tests and its limitations, from setting up the hypotheses to conclusion. It contains one-sided and two-sided test, how to look for critical values in t-distribution, how to make decision whether to reject or do not reject null hypothesis and finally the conclusion whether the estimated beta is statistically significant in explaining the dependent variable at a si...

This video explains the steps in conducting a regression analysis. It also contains the process of empirical research, which is very similar to regression analysis.

Topic 02 EXTRA: How to Manually Generate Estimated Betas using Excel

Topic 02 Ordinary Least Square (OLS) - Part II

Topic 02 Ordinary Least Square (OLS) - Part I

Topic 02 The Seven (7) Classical Assumptions

Topic 02 The Sampling Distribution of Estimated Beta