Udemy – Econometrics Unlocked: Data, Models, and Predictions 2025-2

What you will learn in the course Econometrics Unlocked: Data Models and Predictions

• Understanding the principles of least squares regression: Explaining the algebra of least squares, including trend lines, residuals, predicted values, and R-squared.
• Using software tools for regression analysis: Using Excel and EViews to calculate and interpret trend lines.
• Understand basic concepts of probability: define random variables, expected value, variance, and covariance, and explain their relationship to econometric models.
• Formulating and interpreting linear regression models: understanding the concept of exogeneity and applying Gauss-Markov assumptions to derive OLS estimators.
• Analysis of multivariate regression models: Extending regression analysis to multiple explanatory variables, addressing challenges such as multicollinearity and heterogeneity.
• Modeling and interpreting time series data: Identifying stationary and non-stationary time series data, examining ADL and AR models, and dealing with autocorrelation.
• Detecting and addressing endogeneity: Understanding the implications of endogeneity and applying instrumental variable techniques to estimate parameter constants.
• Examining binary choice models: comparing linear, probit, and logit probability models and applying maximum likelihood estimation.
• Working with panel data: Explain fixed effects and random effects models and use the Hausman test to determine the appropriate model for analyzing panel data.

This course is suitable for people who:

• Are interested in learning the principles of econometrics.
• Seek to understand statistical and economic concepts related to data analysis.
• Need to use statistical software such as Excel and EViews to analyze data.
• They intend to improve their skills in data modeling and forecasting.

Installation Guide

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Quality: 1080p