Say we have a collection of independent random variables $X_0, ... , X_n$, where $X_0 \sim \mathcal{N}(\mu_0, \sigma_0^2)$, but $X_i \sim \mathcal{N}(\mu, \sigma^2)$, for $1 \leq i \leq n$. We characterize the distribution of $R_0 := 1 + \sum_{i=1}^{n} \mathbf{1}\{X_i \leq X_0\}$, the rank of the random variable whose distribution potentially differs from that of the others -- the odd normal out. We show that $R_0 - 1$ is approximately beta-binomial, an approximation that becomes equality as $\sigma/\sigma_0$ or $(\mu-\mu_0)/\sigma_0$ become large or small. The intra-class correlation of the approximating beta-binomial depends on $\Pr(X_1 \leq X_0)$ and $\Pr(X_1 \leq X_0, X_2 \leq X_0)$. Our approach relies on the conjugacy of the beta distribution for the binomial: $\Phi((X_0-\mu)/\sigma)$ is approximately $\mathrm{Beta}(\alpha(\sigma/\sigma_0, (\mu-\mu_0)/\sigma_0), \beta(\sigma/\sigma_0, (\mu-\mu_0)/\sigma_0))$ for functions $\alpha, \beta > 0$. We study the distributions of the in-normal ranks. Throughout, simulations corroborate the formulae we derive.

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