In linear regression, the y-intercept corresponds to which type of error?

In linear regression, the y-intercept corresponds to which type of error?

• A. Constant error
• B. Proportional error
• C. Random error
• D. Systematic error

Answer: (A)

In linear regression, the model is y = β0 + β1x + ε. The intercept β0 is the predicted y when x = 0, acting as a baseline offset. This is a fixed, additive amount that shifts all predicted values by the same amount regardless of x, which is why it corresponds to a constant error. Proportional error would scale with x, random error is the unpredictable scatter around the line, and systematic error refers to a bias in measurements that isn’t the fixed baseline offset captured by the intercept.

In linear regression, the model is y = β0 + β1x + ε. The intercept β0 is the predicted y when x = 0, acting as a baseline offset. This is a fixed, additive amount that shifts all predicted values by the same amount regardless of x, which is why it corresponds to a constant error. Proportional error would scale with x, random error is the unpredictable scatter around the line, and systematic error refers to a bias in measurements that isn’t the fixed baseline offset captured by the intercept.