Finding the mean of $\big(\sum^{n}_{j=1}{X_{ij}}\big)^2$ where $X_{ij}$ is an indicator variable

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Let $n_i$ be the random variable denoting the number of elements placed in bucket $B[i]$ and let $X_{ij}$ be the indicator variable $\mathbb{I}\{A[j] \text{ falls in bucket } i\}$.

Thus, for each $i$, defining $n_{i} := \sum^{n}_{j=1}{X_{ij}}$, we have

$$\mathbb{E}[n^2_i] = \mathbb{E}\left[\left(\sum^{n}_{j=1}{X_{ij}}\right)^2\right].$$

Then I got confused by the two equations below. I don't know how they had this

  • $\mathbb{E}[n^2_i] = \mathbb{E}\left[\left(\sum^{n}_{j=1}{X_{ij}}\right) \left(\sum^{n}_{k=1}{X_{ik}}\right)\right]$
  • $\mathbb{E}[n^2_i] = \mathbb{E}\left[\sum^{n}_{j=1}X_{ij}^2 + \sum_{1\leq j\leq n}{X_{ij}}\sum_{1\leq k\leq n,j \neq k}{X_{ik}}\right]$

Please can someone explain to me how they manage to get the two equations above

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The probability backdrop of this is actually irrelevant, as this is purely about symbolic algebra. First, $$ \left(\sum^{n}_{j=1}{X_{ij}}\right)^2=\left(\sum^{n}_{j=1}{X_{ij}}\right)\left(\sum^{n}_{j=1}{X_{ij}}\right)=\left(\sum^{n}_{j=1}{X_{ij}}\right)\left(\sum^{n}_{k=1}{X_{ik}}\right) $$ where the 2nd equality above is just changing the dummy counter from "$j$" to "$k$" for the second summation. Second, as for why: $$ \left(\sum^{n}_{j=1}{X_{ij}}\right)\left(\sum^{n}_{k=1}{X_{ik}}\right)=\sum^{n}_{j=1}X_{ij}^2 + \sum_{1\leq j\leq n}{X_{ij}}\sum_{1\leq k\leq n,j \neq k}{X_{ik}} $$ you just have multiply out the LHS: $$ \left(\sum^{n}_{j=1}{X_{ij}}\right)\left(\sum^{n}_{k=1}{X_{ik}}\right)=\sum^{n}_{j=1}\left[{X_{ij}}\left(\sum^{n}_{k=1}{X_{ik}}\right)\right]=\sum^{n}_{j=1}\left[X_{ij}^2+X_{ij}\left(\sum_{1\leq k\leq n, k\neq j}{X_{ik}}\right)\right]. $$