No, not from the stated assumptions alone. The centered slope is a weighted sum,
and the weighted errors need not be identically distributed. The ordinary central limit theorem therefore does not apply directly.
For a concrete counterexample, for every choose
These satisfy all three centring and orthogonality assumptions, and both explanatory columns are nonzero. Let the errors be independent with Rademacher distribution, taking values with equal probability. Then
which takes values with probabilities for every . Increasing the sample size adds no information about this slope, and the standardized estimator does not approach a normal distribution.
A useful additional assumption for asymptotic normality of a weighted regression slope is that no single design value dominates:
Under this condition and the given finite error variance, the Lindeberg-Feller central limit theorem yields
justifying the approximation for the slope as well.

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