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Regression Applications

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Regression Applications

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Now · Forecasting

Regression Applications

Forecasting

Use time as a predictor:

y_t = \beta_0 + \beta_1 t + \varepsilon_t

Example: Predict next quarter's sales based on historical trend.

Causal Inference

Regression can estimate causal effects if all confounders are controlled for. Example: Does education affect earnings? Regress earnings on years of education, controlling for ability, experience, and demographics. Warning: "Correlation does not imply causation." Omitted variable bias is a serious concern.

Prediction vs. Inference

Goal	Focus	Key Metric
Inference	Understand relationships	Coefficient estimates, p-values
Prediction	Forecast new outcomes	R-squared, prediction error, cross-validation

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Regression Applications

Regression Applications

Forecasting

Causal Inference

Prediction vs. Inference

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