For , direct multiplication by the sample covariance matrix gives
It is therefore an eigenvector, with eigenvalue . Normalization gives , so the corresponding sample principal component is
Its coefficients are proportional to the required vector. The remaining eigenvalues calculated in (ii) are smaller, confirming that this is the first principal component.

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