OLS Regression in Mathematica: Estimating Income-Consumption Line for 50,000 Households

📝 Description:

In this video, we demonstrate how to estimate the slope and intercept parameters of a simple linear regression model using the Ordinary Least Squares (OLS) method in Mathematica. We use generated monthly data from 50,000 households, with income as the independent variable and consumption as the dependent variable.

Key topics include:

Graphical analysis using scatter plots

Detecting heteroscedasticity in large datasets

OLS estimation using both matrix and non-matrix formulas

Interpreting the Marginal Propensity to Consume (MPC)

Visualizing the regression line over the scatter plot

Mathematica code walkthrough for data import, plotting, and OLS implementation

This is part of our ongoing series on regression analysis. In the next lesson, we’ll explore estimation over different sample sizes extracted from this large dataset.

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Видео OLS Regression in Mathematica: Estimating Income-Consumption Line for 50,000 Households канала EduByAmjad