Question on variance and expectation of Brownian Motion related things

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In a mathematical finance text by Ubbo F Wiersema, I came across the following

Say $\Delta t$ is very small. $\Delta B(t)$ denotes $\textit{brownian motion increment}$. Then $E[\Delta t\Delta B(t)]=0$. $Var[\Delta t\Delta B(t)]=(\Delta t)^2$.

It is also written that $Var[(\Delta B(t))^2]=2(\Delta t)^2$.

How was the calculations of the above two variances done?

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First of all, I think the variance result is wrong, see below.

$\Delta B(t)$ is centered and normally distributed with variance $\Delta t$.

We can rewrite it as $$\Delta B(t)=\sqrt{\Delta t} Y$$ where $Y$ is a standard normal variable.

We know the moments of $Y$ , wich are $E(Y)=0, E(Y^2)=1$ and $E(Y^4)=3$

$$var(\Delta t\Delta B(t))=var(\Delta t\sqrt{\Delta t}Y)=(\Delta t\sqrt{\Delta t})^2*var(Y)=\Delta t^3$$

For the other one, same thing

$$var(\Delta B(t)^2)=var(\Delta t Y^2)=\Delta t^2var(Y^2)$$

WE know that $$var(Y^2)=E(Y^4)-E(Y^2)^2=3-1^2=2$$ Hence, $$var(\Delta B(t)^2)=2\Delta t^2$$