an instrumental variable does: isolates causal effect when you can't randomize

the back-door criterion identifies: sufficient adjustment sets for causal estimation

The back-door criterion identifies sufficient adjustment sets for causal estimation

Controlling for a variable

Confounders influence both treatment and outcome

Causal model

Causal models use DAGs to represent causal relationships

Race and intelligence

IQ test performance differences between racial groups have decreased over time

Bias vs variance: high bias = underfitting, high variance = overfitting

High bias = underfitting, high variance = overfitting

Ridge regression uses L2 to shrink coefficients without eliminating them

Ridge regression minimizes the sum of squared residuals plus L2 penalty λ∑β²