ThmDex – An index of mathematical definitions, results, and conjectures.
Expression for random basic real sum of squares in terms of sample mean and variance
Formulation 0
Let $X_1, \ldots, X_N \in \mathsf{Random}(\mathbb{R})$ each be a D3161: Random real number such that
(i) \begin{equation} N > 1 \end{equation}
(ii) \begin{equation} \overline{X}_N : = \frac{1}{N} \sum_{n = 1}^N X_n \end{equation}
(iii) \begin{equation} S^2_N : = \frac{1}{N - 1} \sum_{n = 1}^N (X_n - \overline{X}_N)^2 \end{equation}
Then \begin{equation} \sum_{n = 1}^N X^2_n = (N - 1) S^2_N + N \overline{X}^2_N \end{equation}
Proofs
Proof 0
Let $X_1, \ldots, X_N \in \mathsf{Random}(\mathbb{R})$ each be a D3161: Random real number such that
(i) \begin{equation} N > 1 \end{equation}
(ii) \begin{equation} \overline{X}_N : = \frac{1}{N} \sum_{n = 1}^N X_n \end{equation}
(iii) \begin{equation} S^2_N : = \frac{1}{N - 1} \sum_{n = 1}^N (X_n - \overline{X}_N)^2 \end{equation}
Writing out the expression $(N - 1) S^2_N$, we have \begin{equation} \begin{split} (N - 1) S^2_N & = \sum_{n = 1}^N (X_n - \overline{X}_N)^2 \\ & = \sum_{n = 1}^N (X^2_n - 2 X_n \overline{X}_N + \overline{X}^2_N) \\ & = \sum_{n = 1}^N X^2_n - 2 \overline{X}_N \sum_{n = 1}^N X_n + N \overline{X}^2_N \\ & = \sum_{n = 1}^N X^2_n - 2 N \overline{X}^2_N + N \overline{X}^2_N \\ & = \sum_{n = 1}^N X^2_n - N \overline{X}^2_N \\ \end{split} \end{equation} Adding $N \overline{X}^2_N$ to both sides we then conclude \begin{equation} (N - 1) S^2_N + N \overline{X}^2_N = \sum_{n = 1}^N X^2_n \end{equation} $\square$