The V-band WMAP temperature data along the prime meridian are consistent with a Gaussian state-space model when the kq75 mask is used to exclude galactic-foreground and point-source HEALPix pixels. A Kalman filter based on this state-space model was used to predict one-step-ahead temperature anisotropies along the meridian. The errors in these predictions are called innovations, which are non-stationary Gaussian white noise according to the model. By standardizing the innovations (dividing them by their theoretical standard deviations), they become stationary (have constant variance), and their statistical properties may be tested rigorously based on the theory of independent, identically-distributed samples. This normal (Gaussian) Quantile-Quantile plot shows that the standardized innovations along the meridian are consistent with a Gaussian state-space model for the temperature anisotropies. The bold blue envelope shows the 2-sigma standard errors of statistical sampling variability for Gaussian innovations. The innovations pass this test because they do not exceed the 2-sigma error envelope.