In a linear regression model: E(Y|X) = b₀ + b₁ * X

When X = 0: E(Y|0) = b₀ + b₁ * 0 = b₀

Where:

• b₀ is the intercept coefficient (y-intercept)
• b₁ is the slope coefficient

Therefore, when the independent variable X equals 0, the expected value of the dependent variable Y is equal to the intercept coefficient b₀. This represents the expected value of Y when X is zero, which is the point where the regression line crosses the Y-axis.