Suppose that the true model is
Yi = βo + β₁Xi + β₂Xi² + εi, 1≤i≤n,
where {εi} are i.i.d. normal random variables with mean zero and variance σ². However, we make a mistake, and fit a simple linear regression model
Yi = βo* + β₁*Xi + β₂Xi + εi*
Write down the ordinary least squares estimator of the slope parameter, de- noted by ⁻β₁*